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- Overview of the Versatile Video Coding (VVC) Standard and its Applications1,890
An overview of the novel technical features for new applications and the core compression technologies for achieving significant bit rate reductions in the neighborhood of 50% over its predecessor for equal video quality and 75% over the currently most-used format, the Advanced Video Coding (AVC) standard are provided.
- Graph Convolutional Label Noise Cleaner: Train a Plug-And-Play Action Classifier for Anomaly Detection587
A graph convolutional network is devised that propagates supervisory signals from high-confidence snippets to low-confidence ones and is capable of providing cleaned supervision for action classifiers.
- StructureFlow: Image Inpainting via Structure-Aware Appearance Flow396
A two-stage model which splits the inpainting task into two parts: structure reconstruction and texture generation is proposed, which shows superior performance on multiple publicly available datasets.
- PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering300
The proposed Portrait Image Neural Renderer can generate photo-realistic portrait images with accurate movements according to intuitive modifications and is extended to tackle the audio-driven facial reenactment task by extracting sequential motions from audio inputs.
- Metabolic reprogramming and therapeutic resistance in primary and metastatic breast cancer245
By targeting distinct metabolic vulnerabilities at both the primary and metastatic stages, new strategies could improve the efficacy of existing therapies and provide better outcomes for breast cancer patients.
- OctAttention: Octree-Based Large-Scale Contexts Model for Point Cloud Compression216
A multiple-contexts deep learning framework called OctAttention employing the octree structure, a memory-efficient representation for point clouds that obtains a 10%-35% BD-Rate gain on the LiDAR benchmark, and saves 95% coding time compared to the voxel-based baseline.
- ROIMIX: Proposal-Fusion Among Multiple Images for Underwater Object Detection187
This work investigates augmentation policies to simulate overlapping, occluded and blurred objects, and builds a model capable of achieving better generalization, called RoIMix, which characterizes interactions among images.
- A digital construction framework integrating building information modeling and reverse engineering technologies for renovation projects163
A digital construction framework that integrates building information modeling (BIM) and reverse engineering (RE) to improve information utilization in different phases and thus reduce mistakes and reworks in renovation projects during urban renewal is proposed.
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- Intra Prediction and Mode Coding in VVC144
The intra prediction and mode coding of the Versatile Video Coding (VVC) standard is presented and a bitrate saving of 25% on average is reported over H.265/HEVC using an objective metric.
- HQ-ISNet: High-Quality Instance Segmentation for Remote Sensing Imagery133
A novel instance segmentation approach of HR remote sensing imagery based on Cascade Mask R-CNN is proposed, which is called a high-quality instance segmentsation network (HQ-ISNet), which exploits a HR feature pyramid network (HRFPN) to fully utilize multi-level feature maps and maintain HR feature maps for remote sensing images’ instances segmentation.
- Coarse-To-Fine Deep Video Coding with Hyperprior-Guided Mode Prediction129
A coarse-to-fine (C2F) deep video compression framework equipped with the new hyperprior-guided mode prediction methods achieves the state-of-the-art performance on HEVC, UVG and MCL-JCV datasets.
- Transform Coding in the VVC Standard126
The experimental results on VVC reference software show that average 4.5% and 3.6% overall coding gain can be achieved by the VVC transform coding tools for All Intra and Random Access configurations, respectively.
- Neural Texture Extraction and Distribution for Controllable Person Image Synthesis100
A neural texture extraction and distribution operation based on double attention that extracts semantic neural textures from reference feature maps and distributes the extracted neural textures according to the spatial distributions learned from target poses to achieve controllable person image synthesis.
- GPA-Net:No-Reference Point Cloud Quality Assessment With Multi-Task Graph Convolutional Network89
To extract effective features for PCQA, a new graph convolution kernel is proposed, i.e., GPAConv, which attentively captures the perturbation of structure and texture, and a multi-task framework consisting of one main task (quality regression) and two auxiliary tasks (distortion type and degree predictions).
- Overview of the Screen Content Support in VVC: Applications, Coding Tools, and Performance87
This paper describes the screen content support and the five main low-level screen content coding tools in VVC: transform skip residual coding (TSRC), block-based differential pulse-code modulation (BDPCM), intra block copy (IBC), adaptive color transform (ACT), and the palette mode.
- 3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation86
Experimental results reveal that the dataset can be utilized to verify and evaluate the aforementioned algorithms, demonstrating the benefits of the proposed dataset.
- Different cardiorespiratory effects of indoor air pollution intervention with ionization air purifier: Findings from a randomized, double-blind crossover study among school children in Beijing83
Ionization air purifier could bring substantial respiratory benefits, however, the potential negative effects on HRV need further investigation.
- Deep Spatial Transformation for Pose-Guided Person Image Generation and Animation82
A differentiable global-flow local-attention framework to reassemble the inputs at the feature level and show that this framework can spatially transform the inputs in an efficient manner.
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- VVC Complexity and Software Implementation Analysis80
A complexity analysis of VVC and its VTM reference software is provided, showing that most of the compression gains of V VC over HEVC can be obtained at a small fraction of the resources needed by the VTM encoder under common test conditions.
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- R-PointHop: A Green, Accurate, and Unsupervised Point Cloud Registration Method74
R-PointHop’s model size and training time are an order of magnitude smaller than those of deep learning methods, and its registration errors are smaller, making it a green and accurate solution.
- Metabolic linkages between indoor negative air ions, particulate matter and cardiorespiratory function: A randomized, double-blind crossover study among children71
Investigating the molecular linkages between indoor NAI, decreased PM and the cardiorespiratory effect after purification found increased NAI and decreased PM improved respiratory function by increasing energy production, improving anti-inflammation and anti-oxidation capacity.
- General Video Coding Technology in Responses to the Joint Call for Proposals on Video Compression With Capability Beyond HEVC71
All technology proposed in the responses to the CfP was based on the classic block-based hybrid video coding design, extending it by new elements of partitioning, intra- and inter-picture prediction, prediction signal filtering, transforms, quantization/scaling, entropy coding, and in-loop filtering.
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- C3DVQA: Full-Reference Video Quality Assessment with 3D Convolutional Neural Network66
A novel architecture, namely C3DVQA, that uses Convolutional Neural Network with 3D kernels (C3D) for full-reference VQA task and empirically found that 3D convolutional layers are capable to capture temporal masking effects of videos.
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- SSD-GAN: Measuring the Realness in the Spatial and Spectral Domains62
This paper introduces SSD-GAN, an enhancement of GANs to alleviate the spectral information loss in the discriminator, and proposes to embed a frequency-aware classifier into the discriminators to measure the realness of the input in both the spatial and spectral domains.
- Overview of the Neural Network Compression and Representation (NNR) Standard58
The NNR standard contains compression-efficient quantization and deep context-adaptive binary arithmetic coding (DeepCABAC) as core encoding and decoding technologies, as well as neural network parameter pre-processing methods like sparsification, pruning, low-rank decomposition, unification, local scaling and batch norm folding.
- Overview of Screen Content Coding in Recently Developed Video Coding Standards58
This paper provides an overview and comparative study of screen content coding technologies, as well as discussions on the performance and complexity of the tools developed in these standards.
- Video-Based Point Cloud Compression Artifact Removal57
This work developed a novel out-of-the-loop point cloud geometry artifact removal solution that can significantly improve reconstruction quality without additional bandwidth cost and jointly recovers both the quantization direction and the quantification noise level by exploiting projection and quantization prior.
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- Performance of two neural network models in bathymetry56
Results based on the root mean square errors and coefficient of determination (R2) show that artificial neural networks outperform the inversion model and the regression tree.
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- Quantitative assessment of the importance of bio-physical drivers of land cover change based on a random forest method47
Using remote sensing data, machine learning, and statistical methods, the spatial and temporal patterns of land cover from 2001 to 2018 in the Loess Plateau of China are analyzed and evapotranspiration was the most important driver and temperature and precipitation had regional heterogeneity, and slope was the least important.
- Pointhop++: A Lightweight Learning Model on Point Sets for 3D Classification45
The PointHop++ method is improved in two aspects: reducing its model complexity in terms of the model parameter number and ordering discriminant features automatically based on the cross-entropy criterion, which is essential for wearable and mobile computing.
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- Association of Genetic Variants With Moyamoya Disease in 13 000 Individuals42
RNF213 rs112735431 and rs148731719 were positively, and TIMP-2 rs8179090, MMP-2rs243865, and M MP-3 rs3025058 were inversely associated with MMD using multiple pathophysiologic pathways.
- Real Photographs Denoising With Noise Domain Adaptation and Attentive Generative Adversarial Network42
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- Information-Growth Attention Network for Image Super-Resolution41
A concise but effective Information-Growth Attention Network (IGAN) is proposed that shows the incremental information is beneficial for SR and outperforms state-of-the-art attention-aware SR approaches.
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- Dendritic Cells and T Cells, Partners in Atherogenesis and the Translating Road Ahead40
This review presents a complete overview, based on existing knowledge of these two cell types in the atherosclerotic microenvironment, and discusses some of the novel means of targeting DCs and T cells as therapeutic tactics for the treatment of atherosclerosis.
- Heart-kidney interactions: mechanistic insights from animal models40
This article focuses on the use of currently available animal models to elucidate mechanistic insights in the clinical cardiorenal phenotype arising from primary cardiac injury, primary renal disease with special emphasis of chronic kidney disease-specific risk factors, and simultaneous cardi Lorenal/renocardiac dysfunction.
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- Bit-depth scalable coding for high dynamic range video38
The proposed inter-layer prediction technique is independent of the forward tone mapping method and is able to cover a wide range of bit-depths and various color spaces.
- Multi-Grained Point Cloud Geometry Compression via Dual-Model Prediction with Extended Octree36
The extended octree, where each partitioned node contains intra-block and extra-block points, is applied to address poor prediction at the node edges of the octree partition, and dual-model prediction fits surfaces and projects residuals onto the surfaces, reducing projection residuals for efficient 2D compression and fitting complexity.
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- Genetic algorithm combined with BP neural network in hospital drug inventory management system35
This study combined the actual situation of hospital drug inventory forecast to build a system model based on hospital drug management mode and analyzed the accuracy and sensitivity of model prediction based on actual conditions and compared the research results with actual data.
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- ICF Generic Set as new standard for the system wide assessment of functioning in China: a multicentre prospective study on metric properties and responsiveness applying item response theory35
The ICF Generic 6 Set can be used for the assessment of functioning in routine clinical practice and an interval score can be derived which is sensitive to change.
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- Visualization of Ligand-Bound Ectodomain Assembly in the Full-Length Human IGF-1 Receptor by Cryo-EM Single-Particle Analysis34
The cryo-EM structure of the ligand-bound ectodomain in the full-length human IGF-1R receptor reveals that only one insulin or one IGF- 1 molecule binds to and activates the full"-length" insulin-like growth factor 1 receptor.
- Texture-Guided Graph Transform Optimization for Point Cloud Attribute Compression33
Experimental results show the proposed texture-guided graph transform optimization scheme for point cloud attribute compression outperforms the state of the art with significant BD-BR gains, surpassing G-PCC by 31.02%, 30.71%, and 32.14% in BD-BR gains for Y, U, and V components.
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- APCCPA '2233
This workshop focuses on point cloud processing, analysis-oriented optimization algorithms for compression and processing, and compression in challenging situations to further improve visual experience and machine vision performance.
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- Overview of HEVC extensions on screen content coding33
The main features and coding technologies in the current HEVC SCC draft standard are reviewed, with discussions about the performance and complexity aspects compared with prior arts.
- LWSNet: A Point-Based Segmentation Network for Leaf-Wood Separation of Individual Trees32
This study extends the leaf-wood separation of tree point clouds in an end-to-end manner and demonstrates that the deep-learning segmentation algorithm has a great potential for processing tree and plant point clouds with complex morphological traits.
- Human epididymis protein 4 in endometrial cancer: A meta-analysis32
The overall analysis suggested that HE4 is a useful diagnostic marker for EC, and may serve as a potential biomarker for EC diagnosis due to certain limitations.
- Advanced Patch-Based Affine Motion Estimation for Dynamic Point Cloud Geometry Compression31
This approach employs a forward-backward jointing ME strategy, generating affine motion-compensated frames for improved inter-geometry references and demonstrates the superiority of the proposed scheme, achieving an average 6.28% geometry bitrate gain over the inter codec anchor.
- PanelNet: Understanding 360 Indoor Environment via Panel Representation31
PanelNet, a framework that understands indoor environments using a novel panel representation of 360 images, is presented and Local2Global Transformer, which aggregates local information within a panel and panel-wise global context is introduced, which greatly improves the model performance with low training overhead.
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- The application of multi-baseline digital close-range photogrammetry in three-dimensional imaging and measurement of dental casts30
Measurements obtained by MBDCRP are compared well with those obtained from plaster casts, indicating that MBD CRP is an alternate way to store and measure dental plaster casts without severe horizontal overlap between any two teeth.
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- Associations of forest negative air ions exposure with cardiac autonomic nervous function and the related metabolic linkages: A repeated-measure panel study29
Short-term exposure to forest NAI is beneficial to HRV, especially to the parasympathetic nerve activity, by successively disturbing different metabolic pathways which mainly reflect the increased anti-inflammation and the reduced inflammation.
- Effect of short-term exposure to particulate air pollution on heart rate variability in normal-weight and obese adults29
Short-term exposure to PM 2.5 /BC is associated with HRV and HR, especially in obese individuals, and the circadian rhythm of HRV should be considered in future studies when HRV is applied.
- Increasing cardiopulmonary effects of ultrafine particles at relatively low fine particle concentrations29
UFP-associated effects on children's cardiopulmonary function persisted even at relatively low PM2.5 concentrations, especially on heart rate variability indices, and UFP control and standard setting should be considered.
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- Neural saliency algorithm guide bi‐directional visual perception style transfer28
The authors render a novel saliency detection algorithm to automatically perceive the visual attention of an image and apply a saliency algorithm to guide the style transferring process, enabling different types of style transferring to occur in different regions.
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- Ntire 2025 Challenge on Short-Form Ugc Video Quality Assessment and Enhancement: Methods and Results26
This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement, and introduces a new short-form UGC dataset tailored for single-image super-resolution, i.e., the KwaiSR dataset.
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- Meta‐analysis of genotype and phenotype studies to confirm the predictive role of the RNF213 p.R4810K variant for moyamoya disease26
The aim of this meta‐analysis study was to assess the predictive effects of RNF213 p.R4810K on phenotype in moyamoya disease (MMD).
- Semantic-Based Building Extraction from LiDAR Point Clouds Using Contexts and Optimization in Complex Environment26
The proposed method first performs a series of preprocessing operations, such as removing ground points, establishing super-points and using them as primitives for subsequent processing, and then semantically labels the raw LiDAR data.
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- Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)25
An unsupervised point cloud registration method, called salient points analysis (SPA), is proposed, which can register two point clouds effectively using only a small subset of salient points.
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- A Heterogeneous Nodes-Based Low Energy Adaptive Clustering Hierarchy in Cognitive Radio Sensor Network24
The simulation results show that the proposed algorithm can not only effectively balance the distribution of CNs among clusters, guaranteeing enough high channel detection probability of each cluster and network energy utilization, but also balance the energy consumption among CHs, eventually prolong the network lifetime.
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- A comparative study of HEVC, VVC, VP9, AV1 and AVS3 video codecs23
The technologies used in recent video codecs are described and their coding performance are compared, including HEVC and VVC developed by the ISO/IEC MPEG and ITU-T VCEG, VP9 developed by Google, AV1 developed by AOM and AVS3 developed by Audio Video coding Standard workgroup of China.
- Meta Learning for Image Captioning23
This work proposes to use a new learning method, meta learning, to utilize supervision from the ground truth whilst optimizing the reward function in RL to improve the propositional content and the distinctiveness of the generated captions.
- Hybrid global–local motion compensated frame interpolation for low bit rate video coding23
Experiments show that the proposed HMCI scheme achieves higher subjective (visual) quality compared to the conventional block-based frame interpolation without global motion compensation, where artifacts in moving backgrounds are significantly reduced.
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- Context-aware Attention Network for Predicting Image Aesthetic Subjectivity22
This work explores a context-aware attention module in two dimensions: hierarchical and spatial that predicts the distribution of human aesthetic ratings of images, which reflects the diversity and similarity of human subjective opinions.
- FeatherWave: An Efficient High-Fidelity Neural Vocoder with Multi-Band Linear Prediction22
The FeatherWave, yet another variant of WaveRNN vocoder combining the multi-band signal processing and the linear predictive coding, is proposed, which can significantly improve the efficiency of speech synthesis.
- Pre-Trained Text Representations for Improving Front-End Text Processing in Mandarin Text-to-Speech Synthesis22
This paper uses pre-trained text encoding models, such as the encoder of a transformer based NMT model and BERT, to extract the latent semantic representations of words or characters and use them as input features for tasks in the front-end of TTS systems.
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- Synthetic self-assembled homogeneous network hydrogels with high mechanical and recoverable properties for tissue replacement22
Inspired by the self-assembly of chemical entities, homogeneous network hydrogels, which contain over 90 wt% water, were synthesized via covalent cross-linking of poly(vinyl alcohol) (PVA) and poly(vineyl pyrrolidone) ( PVP) triggered by microwave-assisted treatment, results in an evenly distributed stress that endures high strains with minimal energy dissipation.
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- Point Cloud Semantic Segmentation with Sparse and Inhomogeneous Annotations20
This work introduces the probability density function into the gradient sampling approximation method to qualitatively analyze the impact of annotation sparsity and inhomogeneity under weakly supervised learning and proposes an Adaptive Annotation Distribution Network capable of robust learning on arbitrarily distributed sparse annotations.
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- TSMD: A Database for Static Color Mesh Quality Assessment Study20
The Tencent – Static Mesh Dataset (TSMD) is created, containing 42 reference meshes with rich visual characteristics, to facilitate the study of static mesh compression algorithm and objective quality metric.
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- Combining Attention with Flow for Person Image Synthesis20
This model not only takes the advantage of the attention operation to generate accurate target structures but also uses the flow-based operation to sample realistic source textures to demonstrate the superiority of the model.
- Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation20
In contrast to supervised backpropagation-based feature learning in deep neural networks (DNNs), an unsupervised feedforward feature (UFF) learning scheme for joint classification and segmentation of 3D point clouds is proposed in this work.
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- A Novel Thresholding Method in Removing Noises of Electrocardiogram Based on Wavelet Transform20
A novel thresholding method based on Discrete Wavelet Transform (DWT) can maintain the geometrical characteristics of ECG signal much better, and it also has higher Signal Noise Ratio (SNR).
- Once-Training-All-Fine: No-Reference Point Cloud Quality Assessment via Domain-Relevance Degradation Description19
A novel NR-PCQA method, Point Cloud Quality Assessment via Domain-relevance Degradation Description (D3-PCQA), which establishes an intermediate domain, the description domain, based on insights from the human visual system (HVS), and decomposes the NR-PCQA problem into two relevant stages.
- Road-Side Individual Tree Segmentation from Urban MLS Point Clouds Using Metric Learning19
A deep learning framework that combines semantic and instance segmentation is proposed to extract single road-side trees from vehicle-mounted mobile laser scanning (MLS) point clouds and achieve better segmentation results than existing published methods in both two urban MLS point clouds.
- ERDN: Equivalent Receptive Field Deformable Network for Video Deblurring19
This work proposes an equivalent receptive field deformable network (ERDN) to perform alignment at the feature level without estimating optical flow, and introduces a dual pyramid alignment module, in which a feature pyramid is constructed to align frames using deformable convolution in a cascaded manner.
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- Deep Learning Geometry Compression Artifacts Removal for Video-Based Point Cloud Compression19
The extensive experimental results show that the proposed approach achieves significant gains on geometry artifacts removal and quality improvement of 3-D point-cloud reconstruction compared to the state-of-the-art schemes.
- Fuzzy Real Option Analysis for IT Investment in Nuclear Power Station19
This paper develops a comprehensive but simple methodology to valuate information technology investment in a nuclear power station based on fuzzy risk analysis and real option approach that can be easily adopted to value any irreversible investment subject to a high degree of uncertainty.
- SJTU-TMQA: A Quality Assessment Database for Static Mesh with Texture Map18
A large-scale textured mesh quality assessment database, namely SJTU-TMQA, is created, which includes 21 reference meshes and 945 distorted samples, and the impact of various types of distortion on human perception is demonstrated.
- GSIP: Green Semantic Segmentation of Large-Scale Indoor Point Clouds18
The proposed GSIP (Green Segmentation of Indoor Point clouds) is green since it has significantly lower computational complexity and a much smaller model size and experiments show that GSIP outperforms PointNet in segmentation performance for the S3DIS dataset.
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- Color Enhancement Using Global Parameters and Local Features Learning18
A neural network to learn global parameters and extract local features for color enhancement and makes it possible to adjust the enhancement intensity by multiplying the enhancement map with a weighting coef-ficient.
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- Global/local motion-compensated frame interpolation for low-bit-rate video18
Experiments show that the proposed scheme can achieve higher overall visual quality compared to conventional block-based frame interpolation schemes.
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- Study On Coding Tools Beyond AV117
A package of coding tools that have been investigated, implemented and tested on top of the codebase, known as libaom, which is used for the exploration of next-generation video compression tools, and a combined coding gain over AV1 is demonstrated.
- Fluorescent sensing of nucleus density assists in identifying tumor cells using an AIE luminogen17
The ability of MASPB to distinguish rare tumor cells from normal cells in malignant pleural effusion samples by virtue of their different cellular distributions is demonstrated, which outshined traditional histochemical stain in contrast.
- Exploiting the Value of the Center-dark Channel Prior for Salient Object Detection17
This article proposes a novel salient object detection algorithm for RGB-D images using center-dark channel priors that performs favorably against most of the state-of-the-art approaches.
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- Associations between personal noise exposure and heart rate variability were modified by obesity and PM2.5: The study among obese and normal-weight adults (SONA)15
Personal exposure to noise was associated with decreased HRV level and imbalanced cardiac autonomic function, as indicated by decreases in standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive intervals (rMSSD), the percentage of R-R intervals that differ from each other by more than 50 ms (pNN50), and increases in LF-HF-Ratio.
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- RailPC: A large‐scale railway point cloud semantic segmentation dataset14
This work introduces RailPC, a new point cloud benchmark that contains twice the number of annotated points compared to the largest available mobile laser scanning (MLS) point cloud dataset and is the first railway‐specific 3D dataset for semantic segmentation.
- Joint effect of multiple air pollutants on cardiometabolic health in normal-weight and obese adults: A novel insight into the role of circulating free fatty acids14
Despite being metabolically healthy, obese subjects have a higher cardiometabolic susceptibility to air pollution, especially O3, and the DNL pathway may represent an intrinsic driver of lipid susceptibility.
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- Recent advances in video coding beyond the HEVC standard14
This paper gives a review of recently developed video coding technologies that have been either adopted into the VVC working draft as part of the standard or under further evaluation for potential inclusions.
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- Trick-Play Optimization for H.264 Video Decoding14
This paper proposes pre- diction schemes named G-Group and Binary Reference GOP Structure, for the H.264/AVC video coding standard to achieve the trick-play functionalities while keep- ing low decoder complexity and memory requirement, and shows that G- group and BRGS are close to the global optimal solutions.
- AIS 2024 Challenge on Video Quality Assessment of User-Generated Content: Methods and Results13
This paper reviews the AIS 2024 Video Quality Assessment (VQA) Challenge, focused on User-Generated Content (UGC), to gather deep learning-based methods capable of estimating the perceptual quality of UGC videos.
- Point Cloud Quality Assessment using 3D Saliency Maps13
This work proposes an effective full-reference PCQA metric which makes an attempt to utilize the saliency information to facilitate quality prediction, called point cloud quality assessment using 3D saliency maps (PQSM).
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- Joint effect of indoor size-fractioned particulate matters and black carbon on cardiopulmonary function and relevant metabolic mechanism: A panel study among school children13
The greatest joint effects of PMs and BC on metabolism were mainly at lag0 and lag01 day, which occurred earlier than the strongest effects on cardiopulmonary function, which were at lag01 and lag02 day.
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- Vaccine-style-net13
Experiments demonstrate that the proposed Vaccine-Style-Net method not only achieves competitive results qualitatively and quantitatively but also can produce a continuous 3D shape with any resolution.
- Deep convolutional neural network for drowsy student state detection13
A novel drowsy student state detection method by integrating deep convolutional neural network is proposed at the first time in the literature and it can effectively reduce the interference of environmental factors in the application scenarios.
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- An Overview of the JPEG AI Learning-Based Image Coding Standard12
An overview of the technical features and characteristics of the JPEG AI standard is provided, designed to ensure broad interoperability, which incorporates various design features to support deployment across diverse devices and applications.
- Perception-Guided Quality Metric of 3D Point Clouds Using Hybrid Strategy12
A perception-guided hybrid metric (PHM) that adaptively leverages two visual strategies with respect to distortion degree to predict point cloud quality and achieves state-of-the-art (SOTA) performance and offers significant performance improvement in multiple distortion environments.
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- A Medical Image Registration Method Based on Progressive Images12
This work develops a coarse-to-fine medical image registration method based on progressive images and SURF algorithm (PI-SURF) for higher registration accuracy and achieves higher quality of registration.
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- RUNX1 Upregulates CENPE to Promote Leukemic Cell Proliferation12
The results indicate a possible mechanism involving the RUNX1-CENPE axis on promoting leukemic cell growth and overexpression in THP-1 human leukemia cells and CD34+ hematopoietic stem/progenitor cells to investigate the biological functions affected by dysregulated RunX1.
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- PAME: Self-Supervised Masked Autoencoder for No-Reference Point Cloud Quality Assessment11
This work proposes a self-supervised pre-training framework using masked autoencoders (PAME) to help the model learn useful representations without labels, and outperforms the state-of-the-art NR-PCQA methods on popular benchmarks in terms of prediction accuracy and generalizability.
- TDMD: A Database for Dynamic Color Mesh Subjective and Objective Quality Explorations11
The Tencent - dynamic colored mesh database (TDMD) is created containing eight reference DCM objects with six typical distortions, making the TDMD the largest available DCM database to the authors' knowledge.
- Residual-guided In-loop Filter Using Convolution Neural Network11
The Residual-Reconstruction-based Convolutional Neural Network (RRNet) is proposed to further improve the coding efficiency to its full extent, where the compression features induced from bitstream in form of prediction residual are fed into the network as an additional input to the reconstructed frame.
- Occupancy-Map-Based Rate Distortion Optimization for Video-Based Point Cloud Compression11
This paper proposes to consider only the rate instead of the rate distortion cost for the unoccupied pixels during the rate distort optimization process and can achieve an average of 11:9% and 15:4% bitrate savings for the geometry and attribute, respectively.
- CNN-Optimized Image Compression with Uncertainty based Resource Allocation11
This approach is a hybrid image coder based on CNN-optimized in-loop filter and mode coding, with uncertainty based resource allocation for compressing the task images, designed for participating the CVPR 2018 Challenge on Learned Image Compression.
- Efficient intracellular delivery makes cancer cells sensitive to nanoemulsive chemodrugs11
It is shown that A549 cells are sensitive to nanoemulsive evodiamine (EVONE) through an efficient intracellular and systematic delivery and the in vivo kinetic, bioavailability and in situ absorption characteristics of EVONE were much better than those of free evodienine.
- Image Watermark Based on Extended Shearlet and Insertion Using the Largest Information Entropy on Horizontal Cone11
This work develops an image watermark algorithm based on the largest information entropy, which tends to obtain preferable invisibility when it is robust against common attacks.
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- Nonlinear motion-compensated interpolation for low-bit-rate video11
Experimental results show that the proposed non-linear enhancement scheme can achieve a higher PSNR value and better visual quality in comparison with traditional methods based only on the linear motion assumption.
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- Intra prediction using multiple reference lines for the versatile video coding standard10
This paper provides a technical overview of the most probable modes (MPM)-based multiple reference line (M-MRL) intra-picture prediction that was adopted into the Versatile Video Coding (VVC) standard draft at the 12th JVET meeting.
- Generative Adversarial Network based Speaker Adaptation for High Fidelity WaveNet Vocoder10
This paper proposes an end-to-end adaptation method based on the generative adversarial network (GAN), which can reduce the computational cost for the training of new speaker adaptation and can further reduce the quality gap between generated and natural waveforms.
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- Tencent Video Dataset (TVD): A Video Dataset for Learning-based Visual Data Compression and Analysis9
- Learning channel-wise spatio-temporal representations for video salient object detection9
Compared with previous works that leverage optical flow or RNNs to utilize temporal cues, the proposed method is simple to implement and offers an intuitive way to understand how spatio-temporal patterns are correlated with salient regions.
- Linear Model Based Geometry Coding for Lidar Acquired Point Clouds9
A linear model that takes the explicit line structures as a prior knowledge to improve the coding efficiency in G-PCC is proposed, and the results have shown that the proposed method is effective in coding point clouds with explicitline structures, such as the Lidar acquired data for autonomous driving.
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- Model checking in Tobit regression via nonparametric smoothing9
This paper proposes a class of lack-of-fit tests for checking the adequacy of a presumed parametric form of the regression function in Tobit regression models, a weighted adaptation of the Zheng's test for fitting a parametric regression model.
- Artificial intelligence–assisted endoscopic diagnosis system for diagnosing Helicobacter pylori infection: a multicenter study8
HOPE AI exhibited robust diagnostic efficacy and interpretability in H. pylori detection, thereby enhancing the efficiency of diagnosis in routine screening contexts and enhancing the efficiency of diagnosis in routine screening contexts.
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- Cognitive Benefits of Reducing Indoor Particulate Matter Exposure During Sleep: New Evidence from a Randomized, Double-blind Crossover Trial8
Reducing PM exposure during sleep resulted in improvements in multiple cognitive domains, with a 0.21 (95% CI: 0.05, 0.36) increase in global cognitive z-score, in which increased sleep oxygen saturation (SpO2) and alterations in dopamine metabolism and histidine metabolism played important roles.
- GeodesicPSIM: Predicting the Quality of Static Mesh With Texture Map via Geodesic Patch Similarity8
Geodesic Patch Similarity (GeodesicPSIM), a novel model-based metric to accurately predict human perception quality for static meshes, is proposed and provided state-of-the-art performance in comparison with image-based, point-based, and video-based metrics on a newly created and challenging database.
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- Comprehensive Analysis of Autophagy-Related Genes in Rice Immunity against Magnaporthe oryzae8
The study highlights the important role of autophagy in rice immunity and suggests that OsATGs may enhance resistance to rice blast fungus through the involvement of SA, JA, or immune-related proteins.
- Evaluating the Effectiveness of Contact-Analog and Bounding Box Prototypes in Augmented Reality Head-Up Display Warning for Chinese Novice Drivers Under Various Collision Types and Traffic Density8
This study examines the effectiveness of the contact-analog graphic compared to the bounding box graphic in various collision types and traffic densities in various collision types and traffic densities.
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- Corner-to-Center long-range context model for efficient learned image compression8
An in-depth analysis of the performance degradation observed in existing parallel context models is conducted, and a proposed Corner-to-Center transformer-based Context Model designed to enhance context and latent predictions and improve rate-distortion performance is proposed.
- Learning knowledge representation with meta knowledge distillation for single image super-resolution8
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- Online Meta Adaptation for Variable-Rate Learned Image Compression8
An online meta-learning (OML) setting for LIC is introduced, which combines ideas from meta learning and online learning in the conditional variational auto-encoder (CVAE) framework, and helps to bridge the gap between the training estimation and true quantized latent distribution.
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- Deep Learning for Visual Data Compression8
The recent progress in deep learning based visual data compression, including image compression, video compression and point cloud compression is introduced.
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- Standardization of medical service indicators: A useful technique for hospital administration8
Standardization method will be helpful to improve the comparability of medical service indicators in hospital administration and will be a practical technique and worthy of promotion.
- Sympathetic mechanisms in an animal model of vasovagal syncope8
Distinct sympathetic activation as represented by left stellate ganglion high-frequency spike discharge activity protected against bradycardia and hypotension in a canine model of vasovagal syncope, and may have therapeutic implications.
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- A Fuzzy Group Decision Approach to Real Option Valuation8
This paper develops a comprehensive but simple methodology for valuating IT investment using real options theory under the fuzzy group decision making environment and discusses the strengths and possible extensions of this hybrid approach to IT investment analysis.
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- Associations of multiple air pollutants with kidney function in normal-weight and obese adults and effect modification by free fatty acids7
Interaction analysis suggested that the associations of air pollutants with kidney function were augmented with TFAs in both groups and weakened with EFAs in the normal-weight group, which has implications for target prevention for kidney dysfunction associated with air pollution, especially among vulnerable population.
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- Guest Editorial Introduction to the Special Issue on Recent Advances in Point Cloud Processing and Compression7
The state-ofthe-art in point cloud processing and compression is getting redefined, yet, many research challenges still remain to be addressed and more sophisticated and efficient algorithms are to be developed.
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- Video-Based Compression for Plenoptic Point Clouds7
This paper introduces a block-based padding method that unifies the unoccupied attribute pixels from different views to reduce their bit cost and proposes encoding them using multiview high efficiency video coding.
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- Adaptive Online Learning of Separable Path Graph Transforms for Intra-Prediction6
A novel adaptive separable path graph-based transform (GBT) that can provide better decorrelation than the DCT for intra-predicted texture data and can significantly outperform H.264/AVC DCT for intra-predicted texture data is introduced.
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- Substitutional Neural Image Compression6
The effectiveness of SNIC, when combined with various neural compression models and target metrics, in improving compression quality and performing bit-rate control measured by rate-distortion curves is demonstrated.
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- FeatherTTS: Robust and Efficient attention based Neural TTS6
The experimental results show that the proposed FeatherTTS not only nearly eliminates the problem of word skipping, repeating in particularly hard texts and keep the naturalness of generated speech, but also speeds up acoustic feature generation by 3.5 times over Tacotron.
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- An Optimized H.266/VVC Software Decoder On Mobile Platform6
The experimental results show that when running on the Apple A14 SoC (iPhone 12pro), the average single-thread decoding speed of the present implementation can achieve 53fps (RA and LB) for full HD (1080p) bitstreams generated by VTM-11.0 reference software using 8bit Common Test Conditions (CTC).
- Learning Model-Blind Temporal Denoisers without Ground Truths6
A novel twin sampler assembles training data by decoupling inputs from targets without altering semantics, which not only solves the noise overfitting problem, but also generates better occlusion masks by checking optical flow consistency.
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- Screen Content Coding in Recently Developed Video Coding Standards6
This tutorial provides an overview and comparative study of screen content coding (SCC) technologies across a few recently developed video coding standards, namely HEVC SCC, VVC, AVS3, AV1 and EVC.
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- Scalable Hash From Triplet Loss Feature Aggregation For Video De-duplication6
A novel content based video segmentation identification scheme that is invariant to the underlying codec and operational bit rates is proposed, it computes robust features from a triplet loss deep learning network that captures the invariance of the same content under different coding tools and strategy, while a scalable hashing solution is developed based on Fisher Vector aggregation of the convolutional features from the Triplet loss network.
- Current Picture Referencing in Versatile Video Coding6
In this paper, several variations of CPR implementations are proposed and discussed, and the one with the best trade-off between coding efficiency and implementation cost has been adopted into the new VVC standard working draft and the reference software VTM.
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- Measurement Properties of Surface Topography for Scoliosis Assessment: A Systematic Review and Meta-analysis5
While the scoliosis angle and asymmetry index demonstrated sufficient criterion validity, challenges remain regarding vertebral rotation validity, responsiveness, and correlations with patient-reported outcomes.
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- Video Coding With Cross-Component Sample Offset5
Inspired by previous cross-component coding algorithms, this paper introduces a novel in-loop filtering approach named Cross-Component Sample Offset (CCSO), which utilizes co-located and neighboring luma samples to generate correction signals for both luma and chroma reconstructed samples.
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- Image enhancement with bi-directional normalization and color attention-guided generative adversarial networks5
A novel bi-directional normalization and color attention-guided generative adversarial network (BNCAGAN) for unsupervised image enhancement that outperforms existing methods, and it can improve both the authenticity and naturalness of low-quality images and thus can be widely used for image retrieval preprocessing to improve the understanding of image semantics.
- Full-Reference Video Quality Assessment for User Generated Content Transcoding5
This work observes that existing full-/no-reference quality metrics fail to accurately predict the perceptual quality difference between transcoded UGC content and the corresponding unpristine references, and proposes a bespoke full-reference deep video quality metric for UGC transcoding.
- PDE-based Progressive Prediction Framework for Attribute Compression of 3D Point Clouds5
This work proposes the partial differential equation (PDE) based progressive prediction framework for attribute compression of 3D point clouds, where the attribute information in the high level is used for interpolating the low level by edge-enhancing anisotropic diffusion to infer local features from the high-level information.
- Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients5
The LASSO model was developed to guide identifying high-risk nonadherent patients and timely and effective interventions to improve their prognosis and survival and demonstrated acceptable discrimination with the area under the ROC curve.
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- Fast sample adaptive offset algorithm for 360-degree video coding5
A fuzzy control based fast SAO method is proposed to reduce the high computational complexity in SAO encoding process according to the characteristics of the ERP format video, and experimental results show that the proposed method can reduce about 73%SAO encoding time on average under the common test conditions with negligible loss.
- BLP - Boundary Likelihood Pinpointing Networks for Accurate Temporal Action Localization5
A novel Boundary Likelihood Pinpointing (BLP) network is proposed to alleviate the deficiency of boundary regression and improve the localization accuracy of state-of-the-art detectors.
- Intra Block Copy for Next Generation Video Coding5
Simulation results show that with all the advanced coding tools enabled beyond the HEVC in the most-up-to-date JVET, the IBC mode can still achieve a significant coding efficiency improvement on screen content test materials.
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- Research on QR Code Black Line and White Line Defect Detection Algorithm5
This paper puts forward a kind of defect detection algorithm based on Hough Transform and vertical projection that can be transplanted to other types of QR code and industrial on-line detection system.
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- SPECT Imaging of Inflammatory Response in Ischemic–Reperfused Rat Hearts Using a 99mTc-Labeled Dual-Domain Cytokine Ligand5
The dual-domain TFI is promising for noninvasive detection of inflammatory reactions in IR myocardium because of its more potent affinity to the inflammatory sites compared with TF and IF.
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- MCI-embedded motion-compensated prediction for quality enhancement of frame interpolation5
A new technique based on motion compensated prediction is investigated in this research to enhance the quality of interpolated frames in frame-rate up-conversion applications and efficient weighting of reference motion vectors is adopted to enhance deformable block-based MCI with four vertex motion vectors.
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- The effect of hypertension, obesity, and type 2 diabetes on lacunar stroke: A network Mendelian randomization study4
This genetic association study found novel independent genetic associations between hypertension and T2D with high risk of lacunar stroke, whereas obesity attenuated the risk of lacunar stroke.
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- Compressed Point Cloud Quality Index by Combining Global Appearance and Local Details4
A full-reference PCQA algorithm tailored for static point clouds is proposed, which can jointly measure geometry and attribute deformations and derive perceptually effective features for the nature of compression distortions and the properties of the human visual system.
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- UR-Net: An Integrated ResUNet and Attention Based Image Enhancement and Classification Network for Stain-Free White Blood Cells4
This work proposes a novel model, UR-Net, which consists of an image enhancement network framed by ResUNet with an attention mechanism and a ResNet classification network that is integrated into the classification model for joint training to improve the classification performance for stain-free WBCs.
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- S3I-PointHop: SO(3)-Invariant PointHop for 3D Point Cloud Classification4
This work focuses on a mathematically transparent point cloud classification method called PointHop, analyzes its reason for failure due to pose variations, and solves the problem by replacing its pose dependent modules with rotation invariant counterparts.
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- GreenPCO: An Unsupervised Lightweight Point Cloud Odometry Method4
It is observed that GreenPCO outperforms benchmarking deep learning methods in accuracy while it has a significantly smaller model size and less training time.
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- FAIVconf: Face Enhancement for AI-Based Video Conference with Low Bit-Rate4
This paper proposes FAIVConf, a specially designed video compression framework for video conferencing, based on the effective neural human face generation techniques, which achieves significant bit-rate reduction in video conference and gives much better visual quality under the same bit- rate compared with H.264 and H.265 coding schemes.
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- Multimedia Analysis and Fusion via Wasserstein Barycenter4
The main idea is to model the ensemble as a problem of Wasserstein Barycenter, where two experimental results show that the ensemble approach outperforms existing methods to a significant extent.
- Boundary Information Matters More: Accurate Temporal Action Detection with Temporal Boundary Network4
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- Perceptual Temporal Incoherence Aware Stereo Video Retargeting4
It is found that properly relaxing temporal constraints for non-paired regions at frame boundaries can effectively mitigate conflicts among depth, shape, and temporal constraints without severely degrading temporal coherence perceptually.
- Extended Shearlet-Based Image Watermarking Algorithm Using Selective Coefficients in Horizontal Cone4
A novel image watermarking method in extended shearlet domain that has good imperceptibility and good robustness against common attacks, such as cropping, JPEG compression and rotation attacks.
- Convergence Analysis of Multilayer Feedforward Networks Trained with Penalty Terms: A Review4
The convergence property and other performance aspects of recently researched training approaches based on different penalization terms are reviewed and the smoothing approximation tricks when the penalty term is non-differentiable at origin are shown.
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- An Empirical Study on Concordance-based English Collocation Teaching4
Empirical support is provided for concordance-based explicit teaching approach's superiority to other approaches in promoting the immediate use and long-term retention of target collocations, which is measured by immediate and delayed test.
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- Neural Network Based Posture Control of a Human Arm Model in the Sagittal Plane4
Posture control of a human arm in the sagittal plane is investigated by means of model simulations and provides novel insight into neural prosthesis control and robotic control.
- Joint temporal-spatial rate control with approximating rate-distortion models4
Good rate-distortion (R-D) models used to approximate empirical R-D curves are developed and the complexity caused by actual encoding is reduced so that the process of finding the optimal/suboptimal solutions is significantly expedited.
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- Bit Allocation for Video Coding with Temporal-Spatial Tradeoff4
Experimental results show that consistency of visual quality has significantly improved as evidenced by the reduced PSNR variance among frames, and the proposed heuristic approach using iterative greedy pruning provides a suboptional solution at a reasonable complexity.
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- Enhancing HDR Video Compression based on Deep Effective Bit Depth Adaptation3
This work improves HDR compression performance using an Effective Bit Depth Adaptation approach (EBDA), which reduces the effective bit depth of the original video content before encoding and reconstructs the full bit depth using a CNN-based up-sampling method at the decoder.
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- Improving Non-Autoregressive Sign Language Translation with Random Ordering Progressive Prediction Pretraining3
A Random Ordering Progressive Prediction Pre-training task for NAR SLT models using CND, enabling the decoder to predict target sequences in diverse orderings and enhancing the modeling of target token dependencies between layers, alleviating the modality gap.
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- Nested multi-scale transform fusion model: The response evaluation of chemoradiotherapy for patients with lung tumors3
The numerical results clearly show that the performance of the proposed method outperforms in comparison with several existing methods, among them, the value of Qabf increased by up to 69%.
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- Learning to Compose Representations of Different Encoder Layers towards Improving Compositional Generalization3
An extension to seq2seq models which learns to compose representations of different encoder layers dynamically for different tasks, since recent studies reveal that the bottom layers of the Transformer encoder contain more syntactic information and the top ones contain more semantic information is proposed.
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- Wedge mode extensions beyond AV1 video codec3
The proposed extended wedge mode features novel components such as relaxed block sizes and number of modes limitation, mathematically derived non-linear based two-dimensional masks for the blending process, and more efficient mode signaling methods.
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- Design and analysis of a novel furnace throat for removing dust particles in flue gas emitted from copper smelting furnace by a computational method3
A two-stage turbulence model of the furnace throat based on the RNG k-ε model combined with the stochastic trajectory model indicates that the furnace throats plays an important role in separating the dust particles from the flue gas by applying centrifugal force and subsequent resistance force.
- Residue guided loop filter for HEVC post processing3
This is the first work that employs residual signal as a vital independent high frequency input to direct the learning of CNN- based loop filtering and implements the proposed algorithms in the HEVC reference software.
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- The Tencent speech synthesis system for Blizzard Challenge 20193
This paper presents the Tencent speech synthesis system for Blizzard Challenge 2019, which performs good in various criteria which indicated the superiority of the system.
- A Novel Contactless Rotary Position Micro-Sensing System Based on Electromagnetism3
The proposed contactless absolute angular position micro-sensor has linear characteristics with accuracy below ±2.5° and linearity with R2 of 0.9992, within the measurement range of 0 to 150°.
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- IT project risk assessment methods: a literature review3
A target-process-oriented framework for classifying IT project risk assessment methods is proposed and a group of 20 methods for assessing risk in IT project are analysed.
- Temporal pattern recognition using spiking neural networks for cortical neuronal spike train decoding3
Spiking neural networks (SNN) which consist of spiking neurons propagate information by the timing of spikes to analyze the cortical neural spike trains directly without temporal information lost demonstrate that temporal coding is a viable code for fast neural information processing.
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- Instance Data Condensation for Image Super-Resolution2
A novel Instance Data Condensation (IDC) framework is proposed, which achieves data condensation in a per-image manner, aiming to address the limitations when directly applying existing DC methods to the ISR task.
- Online-learned graph transforms for adaptive block size intra-predictive coding2
This paper presents a novel block-adaptive separable path graph-based transform (GBT) that is particularly adept at handling such signals and shows significant improvement over the traditional H.264/AVC DCT in processing high-resolution natural images.
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- Brain MR image registration based on an Improved CNN Model2
A brain MR image registration algorithm based on an improved convolutional neural network (CNN) that achieves higher quality of registration.
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- Guest Editorial Introduction to Special Section on Learning-Based Image and Video Compression2
The rapidly increasing consumption of storage capacity and transmission bandwidth from video, especially HD and UHD video content, has made video compression a critical stage to guarantee the quality of delivery and playback.
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- Agent33: An Automated Negotiator with Heuristic Method for Searching Bids Around Nash Bargaining Solution2
This paper designs a negotiating agent that focuses on searching the space of suitable bids that provide high utilities for both sides near the Nash Bargaining Solution (NBS) using a novel heuristic method and finished in the second place in the social welfare category in ANAC 2018.
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- Automatic Clustering Algorithm for Movie Recommendation Based on LFM Model2
The figures show that audience will classify the movies automatically and that the clustering process can be carried out offline, and does not affect the response speed of the recommendation system.
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- The Application of BP Neural Network in Settlement Prediction of Highway Soft Foundation2
It is proved that the BP neural network model is accurate and the settlement has least error.
- Researching and Building of the Education Resources Ontology Based on Metadata2
This paper imports the prototype of the spiral model as the construction method of ontology in the area of education resource, and has built the education resources' ontology.
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- MPEG Video Transcoding with Joint Temporal-Spatial Rate Control2
Simulations show that the proposed rate control method for IPP stream transcoding achieves a higher average PSNR value than the MPEG-4 rate control with a constant frame rate in CBR channels, and can significantly enhance the transcoded video quality in VBR channels, in comparison with straightforward MPEG video transcoding.
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- The mediating role of emotional intelligence in the relationship between nursing work environment and work engagement among nurses in hematopoietic stem cell transplantation wards: a cross-sectional study1
Both the nursing work environment and emotional intelligence significantly influence work engagement among nurses in hematopoietic stem cell transplantation units, suggesting a key mediating role, which can inform strategies for enhancing work engagement in this setting.
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- GroupAC: Inter-Group Context Modeling for Point Cloud Attribute Compression with RAHT1
Experimental results on indoor and outdoor point cloud datasets demonstrate that the proposed GroupAC approach outperforms MPEG G-PCC (TMC13v23) and existing learning-based methods.
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- APP3DV'25: ACM Multimedia - International Workshop on Application-driven Point Cloud Processing and 3D Vision1
This workshop invites innovative contributions in point cloud processing and 3D Gaussian splatting to propel the advancements of 3D vision technologies.
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- Sex-specific differences in reproductive tract lymphomas: epidemiology, clinical features, and treatment outcomes1
Clinical differences were observed between PLFGT and PLMGT; however, the incidence rates in both groups decreased, and combined chemotherapy, radiation, and surgery demonstrated the most effective therapeutic outcomes across both the limited and advanced stages.
- MRSliceNet: Multi-Scale Recursive Slice and Context Fusion Network for Instance Segmentation of Leaves from Plant Point Clouds1
The proposed MRSliceNet framework not only produces clear boundaries and reliable instance identification but also provides an effective solution for automated plant phenotyping, as evidenced by its successful implementation in real-world agricultural research pipelines.
- Diabetes and benign paroxysmal positional vertigo: A 2-sample Mendelian randomization study1
This study found no genetic causal relationship between diabetes type (T1DM or T2DM) and BPPV at the genetic level at the genetic level.
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- Application of Predilution Plasma Exchange: A New Plasmapheresis Method for Self-Anticoagulation, in Liver Failure1
A new method of pre-PE with exogenous donated plasma and a 4% citrate infusion has higher safety than post-PE using exogenous donated plasma and a 4% citrate infusion, although it decreases the solute clearance efficiency slightly.
- Mendelian randomization analysis reveals the causal relationship between immune cells and leukemia1
The results of this investigation reveal that leukemia closely relates to specific types of immune cells, and provides a scientific basis for further investigations into factors that will improve immunotherapy.
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- Advanced transform coding methods for next-generation video coding beyond AV11
The proposed methods enable the encoder to optimize transform sets for each intra prediction residual block and extend the use of secondary transforms for inter prediction residuals to both intra and inter coded blocks.
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- GPCGC: A Green Point Cloud Geometry Coding Method1
A low-complexity point cloud compression method called the Green Point Cloud Geometry Codec (GPCGC), is proposed to encode the 3D spatial coordinates of static point clouds efficiently and offers a coding performance competitive with MPEG's V-PCC and G-P CC standards at significantly lower complexity.
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- Robust Corner Detection Using Linear Fitting Error Estimation1
The experimental results show that the proposed corner detection algorithm outperforms the five state-of-the-art corner detection methods in terms of localization error and average repeatability.
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- Stationary Tetrolet Transform: an Improved Algorithm for Tetrolet Transform1
Experimental results show that compared with traditional algorithm, the proposed algorithm can get better sparse representation and eliminate the blocking artifacts in image processing resulted from tetrolet transform algorithm.
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- Research on P2P Caching Mechanism Based on the Request and Probability1
The simulation experiment demonstrates that the caching mechanism designed based on the request and probability can significantly improve the caching hit ratio and reduce the number of query jump, thereby opti- mizing the performance of caching mechanism.
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- Abnormal Crowd Movement Direction Detection Algorithm1
A new algorithm is proposed in this paper which detects the direction of abnormal crowd movement effectively and can avoid danger caused by messy movement.
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- Further Study on the Evaluation of Information by Entropy1
The inherent characters of information from three different directions, defined the concepts of sensitivity, value sensitivity and precision of information to compare different information and make it possible to evaluate information scientifically.
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- Editorial for Special Issue on Three-dimensional Point Cloud Data Modeling, Processing, and Analysis–
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- Overfitted Point Cloud Attribute Codec Using Sparse Hierarchical Implicit Neural Representations–
This work introduces a novel vertex-based INR framework, which integrates interpolation to enable accurate and compact implicit representations of point cloud attributes, and develops efficient level-wise entropy models to exploit dependencies within and across hierarchical levels.
- Efficient texture coordinate prediction guided by mesh geometry–
A strategy to efficiently predict the texture coordinates for 3D mesh compression by exploring the impact of different dihedral angles of adjacent geometric triangles to texture coordinate prediction and proposing a strategy that switches to suitable algorithm for better prediction.
- Pathological diagnosis experience and literature review of four cases suspected Lynch-like syndrome–
Extraintestinal tumors associated with Lynch-like syndrome mostly exhibit histopathological characteristics and MMR/MSI changes similar to classic Lynch syndrome, but without pathogenic germline MMR mutations or MLH1 promoter methylation.
- Efficient coding of repeated mesh connected components via connectivity skip and prediction refinement–
A prediction refinement scheme is proposed in which the residue of an already encoded vertex improves the prediction of its corresponding vertex in another connected component within the same group.
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- Encoding, decoding, and rendering pipeline for multiview streaming and display in VR using VVC–
This work presents a VVC-based pipeline for multiview streaming and display in VR, focusing on bitrate allocation, adaptive streaming, and real-time decoding and rendering optimizations.
- Clinical characteristics and outcomes among patients with subcutaneous panniculitis-like T-cell lymphoma–
SPTCL has unique clinical and pathological characteristics and tends to occur in younger patients, particularly among individuals aged ≥ 50, with peak incidence in the 60–69-year age group.
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- Efficient determination of orientable manifold polygon meshes–
An efficient algorithm to determine whether a polygon mesh - or any of its connected components (CCs) - is an orientable 2-manifold and its effectiveness in polygon mesh compression is applied.
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- Study on the mechanical parameters of neuromuscular joint facilitation rehabilitation techniques for lumbar intervention–
This study confirmed that the measurement of the force on the spinous process in lumbar neuromuscular joint facilitation using mechanical measurement gloves has good reliability.
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- Advancements in intra prediction techniques beyond AV1 codec–
Extensions to smooth prediction modes and angular intra prediction modes to improve the intra coding performance towards a next-generation video codec beyond the AV1 codec are proposed.
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- LKB1 Positively Regulates Dendritic Cell-induced T Cell Immunity and Suppresses Tumor Development.–
The data suggest that LKB1 can enhance DC-mediated T cell immunity by restraining Treg development and thereby suppressing tumor growth.
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- Image Encryption Based on A Novel Memristive Chaotic System with Super Wide Range and Multiple Image Morphing–
The memristor-based chaotic system has a special attractor and the maximum Lyapunov exponent of the system is increasing gradually in , and the Latin-cube based scrambling method is improved to enhance the generalizability of the cryptographic algorithm.
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- Subjective and objective study of sharpness enhanced UGC video quality–
A statistical model is proposed to precisely measure whether the quality of UGC videos is enhanced or degraded and benchmark state-of-the-art No-Reference image or video quality metrics with the collected subjective data.
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- FDBP-InSAR: An Efficient Algorithm for InSAR Imaging via Frequency Domain Back Projection–
This paper proposes an efficient InSAR imaging method, called a frequency-domain back-projection algorithm (FDBPA), to achieve high-resolution focusing and accurate phase-preserving of InSar imaging and demonstrates the efficiency and high-quality imaging of the FDBPA method.
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- A case of atrioventricular junction ablation and permanent left bundle branch pacing for patient with refractory atrial fibrillation and hypertrophic cardiomyopathy–
This case originally confirmed that the combination of AVJA and LBBP, without the defect of AVNA combined with HBP, is a better strategy with feasibility and safety for refractory AF patients with comorbidity of HCM, additionally, it may make LBBB more applicable and valuable among patients suffering from HCM meanwhile pace maker treatments are essential.
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- Combined Compact Difference Scheme for Solving Unsteady Convection-Diffusion Equations–
A boundary scheme is constructed that matches the interior point and a stable combination semi-discrete compact scheme is obtained which is discretized by the third-order Runge-Kutta method in the time direction.
- Design and Analysis of Object Behavior in Media Content-User Relationship Network Model–
Using the theory of complex network and the Agent theory, the attribute information of media content and web users are analyzed, the objects and object clusters are classified and defined, and the behavior mechanism of related objects is designed and analyzed to realize the intelligence of the relationship network.
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- Fast total variation-based image restoration using blockwise accelerated proximal gradient approach–
A blockwise accelerated proximal gradient approach that chooses a block diagonal Lipschitz matrix in the generalized APG algorithm, such that the subproblems can be solved either by fast Fourier transform (FFT) or in closed forms.
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- Effects of selective ablation of the ligament of Marshall attenuated acute atrial electrical remodeling via decreasing cardiac sympathetic nerve activity–
Selective ablation LOM can attenuate atrial electrical remodeling induced by 6 h-RAP and the possible mechanism might be related to the modulation of cardiac autonomic nervous activity.
- Verification testing of the compression performance of the HEVC screen content coding extensions–
Verification testing of the coding performance of the screen content coding (SCC) extensions of the High Efficiency Video Coding (HEVC) standard shows a very substantial benefit in coding efficiency for the SCC extensions, and provided consistent results with a high degree of confidence.
- Hyperspectral Images Classification via Weighted Spatial-Spectral Principle Component Analysis–
The new method, Weighted Spatial and Spectral Principle Component Analysis (WSSPCA), not only can lower the influence of singular point in HSI, but also reduce the redundancy between bands, which improves the HSI classification accuracy efficiently.
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- Research on Fuzzy Classification Model for Mapping Data–
A modified fuzzy classification method for mapping data that is more universal and the result of classification is more impersonal than the traditional classification methods.
- Establishment of Callus Regeneration System of English Lavender–
It was shown that the induction results of the MS +2,4-D + KT0.30 mg/L medium groups were better than that of other groups and the rooting rate reached 33% in 20 days.
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- On the professional competence of librarians of digital book library in Internet age–
The increasing popularity of Internet has necessitated the transformation of traditional libraries into digital book libraries, which poses challenges to traditional management of library and calls for its reform with customer-oriented service as the guiding line.
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- Scientific Management of Network Education Resource–
A comparatively mature and complete model for the management system of network education resource is recommended, an idea of designing and constructing the instructional database for Tianjin Radio and TV University is introduced, and the importance of implementing Technical Standard for Education Resource Management is emphasized.
- Efficient MPEG-2 to MPEG-4 video transcoding–
Simulations show that the proposed MPEG-2 to MPEG-4 video transcoder with rate control can out-perform the basic MPEG transcoder that adjusts the re-quantization step size at a constant frame rate.
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- Joint temporal-spatial quality enhancement for full frame-rate video playback–
A joint temporal-spatial rate control scheme is investigated to optimize temporal and spatial rate-distortion (R-D) performances for full frame-rate video playback, where skipped frames are reconstructed via frame interpolation by reconstructing skipped frames with bidirectional motion-compensated interpolation.
- Mathematical Technique of Data Mining Based on Web Structure–
Web structure data mining employs the conventional mathematical technique-linear equation to express structure relationship between Web pages and uses the solution of linear equation to find out page rank of Wed page which proves that important Web page in Web structure can be used to improve the prop erty of the search engine.
- An Algorithm of Generating the Binary-sort-tree on the New Structure–
A study of an algorithm of generating the binary-sort-tree on the new structure and an analysis is made of the time complexity that can help to improve tree-operation both in time and in space.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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