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- Dense Nested Attention Network for Infrared Small Target Detection1,048
This paper designs a dense nested interactive module (DNIM) to achieve progressive interaction among high-level and low-level features and proposes a cascaded channel and spatial attention module (CSAM) to adaptively enhance multi- level features.
- Unsupervised Degradation Representation Learning for Blind Super-Resolution419
This paper proposes an unsupervised degradation representation learning scheme for blind SR without explicit degradation estimation, and introduces a Degradation-Aware SR (DASR) network with flexible adaption to various degradations based on the learned representations.
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- Learning Parallax Attention for Stereo Image Super-Resolution320
A parallax-attention mechanism with a global receptive field along the epipolar line to handle different stereo images with large disparity variations is introduced and a new and the largest dataset for stereo image SR is proposed.
- MTU-Net: Multilevel TransUNet for Space-Based Infrared Tiny Ship Detection316
A vision Transformer (ViT) convolutional neural network (CNN) hybrid encoder to extract multilevel features and a FocalIoU loss to achieve both target localization and shape description are designed.
- Spatial-Angular Interaction for Light Field Image Super-Resolution208
Experimental results demonstrate the superiority of LF-InterNet over the state-of-the-art methods, i.e., the method can achieve high PSNR and SSIM scores with low computational cost, and recover faithful details in the reconstructed images.
- Recent progress in biomedical applications of persistent luminescence nanoparticles200
PLNPs are demonstrated to be a newly-emerging class of functional materials with unprecedented advantages in biomedicine and can guide cancer therapy with a high signal-to-noise ratio (SNR) and superior sensitivity.
- Light Field Image Super-Resolution With Transformers190
This paper proposes a simple but effective Transformer-based method for LF image SR, designed to incorporate complementary information among different views, and achieves superior SR performance with a small model size and low computational cost.
- A Difunctional Regeneration Scaffold for Knee Repair based on Aptamer‐Directed Cell Recruitment187
An aptamer-bilayer scaffold is designed for autologous mesenchymal stem cell recruitment and osteochondral regeneration that can efficiently recruit MSCs to the defect and induce the directional differentiation of M SCs, thus successfully achieving simultaneous regeneration of cartilage and bone in the knee joint.
- Bioinspired extracellular vesicles embedded with black phosphorus for molecular recognition-guided biomineralization186
The authors report on bioinspired matrix vesicles loaded with black phosphorus nanosheets and cell-specific aptamers for bone regeneration and demonstrate bone defect repair in vivo.
- New insights into the structure–performance relationships of mesoporous materials in analytical science175
The structural properties of mesoporous materials that can be optimized to improve the analytical performance are discussed.
- Deformable 3D Convolution for Video Super-Resolution170
A deformable 3D convolution network (D3Dnet) is proposed to incorporate spatio-temporal information from both spatial and temporal dimensions for video SR, and achieves state-of-the-art SR performance.
- Learning A Single Network for Scale-Arbitrary Super-Resolution162
This paper develops a plug-in module for existing SR networks to perform scale-arbitrary SR, which consists of multiple scale-aware feature adaption blocks and a scale- aware upsampling layer that enables the network to adapt to arbitrary scale factors.
- Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection with Single Point Supervision159
This paper proposes a label evolution framework named label evolution with single point supervision (LESPS) to progressively expand the point label by leveraging the intermediate predictions of CNNs, and shows that CNNs equipped with LESPS can well recover the target masks from corresponding point labels.
- Parallax Attention for Unsupervised Stereo Correspondence Learning159
A generic parallax-attention mechanism (PAM) to capture stereo correspondence regardless of disparity variations is proposed and Experimental results show that the PAM is generic and can effectively learn stereo correspondence under large disparity variations in an unsupervised manner.
- Photon-Responsive Antibacterial Nanoplatform for Synergistic Photothermal-/Pharmaco-Therapy of Skin Infection157
A photon-controlled antibacterial platform designed by encapsulating black phosphorus quantum dots and pharmaceuticals inside a thermal-sensitive liposome can open new possibilities for avoiding bacterial resistance and efficiently killing antibiotic-resistant bacteria, making it valuable in fields ranging from antiinfective therapy to precision medicine.
- Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution155
This letter proposes a light field refocusing method that can selectively refocus images with focused region being superresolved and bokeh being esthetically rendered and enables postadjustment of depth of field.
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- Direction-Coded Temporal U-Shape Module for Multiframe Infrared Small Target Detection145
A simple yet effective direction-coded temporal U-shape module (DTUM) for MIRST detection and a motion-to-data mapping to distinguish the motion of targets and clutters by indexing different directions, which achieves the state-of-the-art performance in detecting infrared small and dim targets and suppressing false alarms.
- Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark145
A large-scale satellite video dataset with rich annotations for the task of moving object detection and tracking is built and a motion modeling baseline is introduced to improve the detection rate and reduce false alarms.
- A Stereo Attention Module for Stereo Image Super-Resolution143
Using SAM, the generic stereo attention module (SAM) is proposed to extend arbitrary SISR networks to stereo images and can exploit cross-view information while maintaining the superiority of intra-View information exploitation, resulting in notable performance gain to SisR networks.
- Recent progress in background-free latent fingerprint imaging128
This review is organized around background-free LFP imaging based on the difference in optical properties between contrast agents and background compounds: (i) different excitation wavelengths, (ii) different emission wavelengths, (-) different luminescence lifetime values, (iv) different plasmonic properties, (v) different photothermal properties, and (vi) different electrochemiluminescence properties.
- Nonconvex Tensor Low-Rank Approximation for Infrared Small Target Detection120
This paper proposes a non-convex tensor low-rank approximation (NTLA) method for infrared small target detection, which has strong robustness and low false-alarm rate and proposes asymmetric spatial-temporal total variation (ASTTV) regularization to achieve more accurate background estimation in complex scenes.
- Occlusion-Aware Cost Constructor for Light Field Depth Estimation114
A simple and fast cost constructor to construct matching cost for LF depth estimation, composed by a series of convolutions with specifically designed dilation rates, which is occlusion-aware and can handle occlusions by dynamically modulating pixels from different views.
- Time-Gated Imaging of Latent Fingerprints and Specific Visualization of Protein Secretions via Molecular Recognition114
Results proved the potent ability of Zn2GeO4:Ga,Mn in eliminating background fluorescence to afford highly sensitive LFP imaging and provides great versatility in LFP Imaging and good potential in uncovering the chemical information within LFP, making it valuable in forensic investigations and medical diagnostics.
- Symmetric Parallax Attention for Stereo Image Super-Resolution112
This paper proposes a symmetric bi-directional parallax attention module (biPAM) and an inline occlusion handling scheme to effectively interact cross-view information and designs a Siamese network equipped with a biPAM to super-resolve both sides of views in a highly symmetric manner.
- Learning Non-Local Spatial-Angular Correlation for Light Field Image Super-Resolution102
This paper adopts the epipolar plane image (EPI) representation, develops a Transformer network with repetitive self-attention operations to learn the spatial-angular correlation, and develops a Transformer network with repetitive self-attention operations to learn the spatial-angular correlation.
- An Ultrasensitive Diagnostic Biochip Based on Biomimetic Periodic Nanostructure-Assisted Rolling Circle Amplification96
The PCs-RCA biochip can detect bioactive molecules with ultrahigh sensitivity and good specificity, making it valuable in clinical disease diagnosis and health assessment.
- Arbitrary-Oriented Ship Detection Through Center-Head Point Extraction95
This article introduces a new dataset for multiclass arbitrary-oriented ship detection in remote sensing images at a fixed ground sample distance (GSD) that is named FGSD2021 and proposes a center-head point extraction-based detector (CHPDet), which achieves the state-of-the-art performance and can well distinguish between bow and stern.
- Adiponectin AS lncRNA inhibits adipogenesis by transferring from nucleus to cytoplasm and attenuating Adiponectin mRNA translation95
AdipoQ antisense (AS) lncRNA was first identified, and it was found that it inhibited adipogenesis and was a novel therapeutic target for obesity-related metabolic diseases.
- DeOccNet: Learning to See Through Foreground Occlusions in Light Fields94
This paper handles the LF de-occlusion (LF-DeOcc) problem using a deep encoder-decoder network (namely, DeOccNet), and is the first deep learning-based LF-De Occ method.
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- A Systematic Survey of Deep Learning-Based Single-Image Super-Resolution79
This survey gives an overview of DL-based SISR methods and group them according to their design targets and presents the reconstruction results of some classic SISR methods to intuitively know their performance.
- Naked eye detection of multiple tumor-related mRNAs from patients with photonic-crystal micropattern supported dual-modal upconversion bioprobes79
A biochip-based mRNA detection device is designed by combining a hydrophilic–hydrophobic micropattern with upconversion luminescence (UCL) probes.
- Highly Sensitive Detection of Bladder Cancer-Related miRNA in Urine Using Time-Gated Luminescent Biochip77
An ultralow background biochip based on time-gated luminescent probes supported by photonic crystals (PCs) was successfully developed for detection of BC-related miRNA biomarkers with high sensitivity and specificity in urine samples.
- Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines75
This paper builds the first large-scale benchmark with high diversity for RGBT SOD (namely RGBT-Tiny), including 115 paired sequences, 93 K frames and 1.2 M manual annotations and proposes a scale adaptive fitness (SAFit) measure that exhibits high robustness on both small and large objects.
- You Only Train Once: Learning a General Anomaly Enhancement Network With Random Masks for Hyperspectral Anomaly Detection70
This article achieves a general anomaly enhancement network for hyperspectral AD that only needs to be trained once and achieves the optimal balance between detection accuracy and inference speed among state-of-the-art AD methods.
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- Motion and Appearance Decoupling Representation for Event Cameras61
Inspired by human visual prior, a motion and appearance decoupling (MAD) event representation is proposed to disentangle the mixed spatial-temporal event tensor into two independent branches to reduce the network’s learning burden toward complex high-level interpretation tasks.
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- Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection60
This work proposes the first method to achieve SIRST detection with single-point supervision, and can accurately recover pseudo masks and thus turn arbitrary fully supervised SIRST detection networks into weakly supervised ones with only single point annotation.
- Learning Sub-Pixel Disparity Distribution for Light Field Depth Estimation59
This paper proposes a simple yet effective method to learn the sub-pixel disparity distribution by fully utilizing the power of deep networks, especially for LF of narrow baselines and designs an uncertainty-aware focal loss to supervise the predicted disparity distribution toward the ground truth.
- Local Motion and Contrast Priors Driven Deep Network for Infrared Small Target Superresolution59
This article proposes the first infrared small target SR method named local motion and contrast prior driven deep network (MoCoPnet) to integrate the domain knowledge of therared small target into deep network, which can mitigate the intrinsic feature scarcity of infrared small targets.
- Gated Recurrent Multiattention Network for VHR Remote Sensing Image Classification57
A gated recurrent multiattention neural network (GRMA-Net) that uses multilevel attention modules to focus on informative regions to extract more discriminative features and is fed into a deep-gated recurrent unit (GRU) to capture long-range dependency and contextual relationship.
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- Real-World Light Field Image Super-Resolution Via Degradation Modulation55
Compared with existing state-of-the-art single and LF image SR methods, the proposed method achieves superior SR performance under a wide range of degradation, and generalizes better to real LF images.
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- Emerging Biomimetic Applications of DNA Nanotechnology54
This Forum Article summarizes recent developments of DNA nanotechnology in mimicking the structures and functions of existing cellular components and focuses on the construction of higher-order structures by DNA nan technology to recreate cell-like structures.
- NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results52
The first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4, develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development.
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- Deep Bilateral Learning for Stereo Image Super-Resolution50
This letter uses a parallax-attention module to incorporate information from left and right views to learn content-aware bilateral filters, which are used to recover missing details at different spatial locations while preserving stereo consistency in a bilateral stereo super-resolution network.
- Dense Dual-Attention Network for Light Field Image Super-Resolution48
A view attention module is designed to adaptively capture discriminative features across different views and a channel attention module to selectively focus on informative information across all channels to improve SR performance.
- DARDet: A Dense Anchor-Free Rotated Object Detector in Aerial Images48
This letter proposes a dense anchor-free rotated object detector (DARDet) for rotated object detection in aerial images that achieves state-of-the-art performance on three commonly used aerial objects datasets (i.e., DOTA, HRSC2016, and UCAS-AOD) while keeping high efficiency.
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- Infrared Small Target Detection in Satellite Videos: A New Dataset and a Novel Recurrent Feature Refinement Framework40
A recurrent feature refinement (RFR) framework as the baseline method for satellite motion estimation and compensation and the comparative results show that ResUNet equipped with RFR outperforms the state-of-the-art MIRST detection methods.
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- Self-Supervised Deep Subspace Clustering for Hyperspectral Images With Adaptive Self-Expressive Coefficient Matrix Initialization39
An end-to-end trainable network for HSI clustering, where the cluster assignments with high confidence are employed as pseudo-labels to supervise the feature learning process and an adaptive self-expressive coefficient matrix initialization strategy is designed to reduce the dictionary redundancy.
- Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos38
This paper proposes a novel framework called HGT-Track (Heterogeneous Graph Transformer based Multi-Tiny-Object Tracking), and introduces the first benchmark VT-Tiny-MOT (Visible-Thermal Tiny Multi-Object Tracking) for RGB-T fused multiple tiny object tracking.
- Bioactive Core–Shell CaF2 Upconversion Nanostructure for Promotion and Visualization of Engineered Bone Reconstruction38
A synergistic nanodepot based on a bioactive core-shell CaF2 upconversion nanostructure that integrates multiple mineral ions for metabolic regulation was built for the acceleration and monitoring of the biomineralization process.
- NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results35
The 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new solutions and results establishes a new benchmark for stereo image SR.
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- SpecDETR: A transformer-based hyperspectral point object detection network33
This paper introduces SpecDETR, the first specialized network for hyperspectral multi-class point object detection, which eliminates dependence on pre-trained backbone networks commonly required by vision-based object detectors and outperforms SOTA visual object detection networks and HTD methods.
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- Probing Deep Into Temporal Profile Makes the Infrared Small Target Detector Much Better29
This paper remodels the IRST detection task as a one-dimensional signal anomaly detection task, and proposes an efficient deep temporal probe network (DeepPro) that only performs calculations in the time dimension for IRST detection, which outperforms existing state-of-the-art IRST detection methods on widely-used benchmarks with extremely high efficiency.
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- OccCasNet: Occlusion-Aware Cascade Cost Volume for Light Field Depth Estimation27
This work proposes an occlusion-aware cascade cost volume for LF depth (disparity) estimation and introduces occlusion maps to enhance accuracy in constructing the occlusion-aware cost volume, allowing the refined disparity estimation network to yield a more precise disparity map.
- Dual-Aptamer-Conjugated Molecular Modulator for Detecting Bioactive Metal Ions and Inhibiting Metal-Mediated Protein Aggregation27
The approach provides a promising tool for detecting bioactive metal ions and studying the molecular mechanisms behind life activities and can inhibit the generation of Zn2+-triggered Aβ aggregates due to the trapping of ZN2+ around Aβ species.
- Surface ligand-assisted synthesis and biomedical applications of metal–organic framework nanocomposites26
The surface ligand-assisted synthesis and biomedical applications of MOF nanocomposites are comprehensively reviewed and surface ligands, molecules with surfactant-like properties, are demonstrated to exhibit the robust capability to modify the interfacial properties of nanomaterials.
- Artesunate Induces Ferroptosis in Hepatic Stellate Cells and Alleviates Liver Fibrosis via the ROCK1/ATF3 Axis26
The ROCK1/ATF3 axis was involved in liver fibrosis and regulation of ferroptosis, which provides an experimental basis for further study of Art for the treatment of liver fibrosis.
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- Incorporating Deep Background Prior Into Model-Based Method for Unsupervised Moving Vehicle Detection in Satellite Videos25
A deep background prior is obtained by a background reconstruction network, which can learn to reconstruct the background from consecutive frames, and can be trained in an unsupervised way by introducing specifically designed loss, thus relieving the dependence on large-scale labeled datasets.
- Learning Remote Sensing Object Detection With Single Point Supervision25
This article designs a point label upgrader (PLUG) to generate pseudo-box labels from single-point labels and then uses the pseudo-boxes to supervise the optimization of existing detectors and proposes a sparse feature-guided semantic prediction (SemPred) module that can generate high-quality semantic maps.
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- Efficient Chiral Nanosenor Based on Tip-Modified Nanochannels24
A chiral nanosensor based on an artificial tip-modified nanochannel system that allows efficient selective recognition of chiral drugs and the selective coefficient of this system toward R-propranolol is higher than the traditional fully modified nanochannels in this work.
- Unsupervised Degradation Representation Learning for Unpaired Restoration of Images and Point Clouds23
- NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results23
This paper summarizes the 3rd NTIRE challenge on stereo image super-resolution with a focus on new solutions and results and establishes a new benchmark for stereo image SR.
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- Specific muscle targeted delivery of miR-130a loaded lipid nanoparticles: a novel approach to inhibit lipid accumulation in skeletal muscle and obesity19
Results indicated LNP@miR-130a is a promising inhibitor of skeletal muscle lipid deposition and may help alleviate obesity, which provides new insights for obesity treatment and lays foundation for the development of targeted skeletal muscle therapeutics.
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- Disparity Estimation for Camera Arrays Using Reliability Guided Disparity Propagation19
This paper proposes a method to estimate the disparity from camera arrays by introducing a novel prior and inferring the corresponding implementation algorithm named reliability guided disparity propagation (RGDP).
- A new approach to kinematic feature extraction from the human right ventricle for classification of hypertension: a feasibility study19
The features are shown to be consistent and converging towards intrinsically physiological components for the heart, and may potentially represent a new set of features for classifying the progressive change in RV function caused by PH, particularly in comparison to traditional clinical metrics.
- Enhancing Mid–Low-Resolution Ship Detection With High-Resolution Feature Distillation17
A feature distillation framework to fully exploit the information in ground-truth HR images to handle mid–low-resolution ship detection and can outperform several state-of-the-art detection methods in terms of mAP50 and mAP75.
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- LFSRDiff: Light Field Image Super-Resolution via Diffusion Models16
LFSRDiff is introduced, the first diffusion-based LF image SR model, by incorporating the LF disentanglement mechanism, enabling more effective extraction and fusion of both spatial and angular information within LF images.
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- Diving Into Epipolar Transformers for Light Field Super-Resolution and Disparity Estimation14
This paper focuses on orthogonal epipolar geometry of LF images and proposes a generic Epipolar Transformer mechanism that incorporates geometrically meaningful correlations along the epipolar lines, and explores the use of geometry information encoded in the Epipolar Transformer to directly regress the disparity results, effectively avoiding the limitation of a fixed maximum disparity.
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- Fast Convergence Strategy for Multi-Image Superresolution via Adaptive Line Search13
An adaptive line search strategy to realize the fast convergence of reconstruction-based SR, where the approximate analytical expression of step size is introduced to prevent us from setting it empirically or running iterations to test a proper one.
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- SPTrack: Spectral Similarity Prompt Learning for Hyperspectral Object Tracking12
A spectral similarity prompt learning approach for hyperspectral object tracking (SPTrack) is proposed, which introduces a spectral matching map based on spectral similarity, which converts 3D hyperspectral data with different spectral bands into single-channel hotmaps, thus enabling cross-spectral domain generalization.
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- Transcriptome and metabolome analyses reveal the key genes related to grain size of big grain mutant in Tartary Buckwheat (Fagopyrum tartaricum)11
This combined comprehensive analysis identified 24 potential candidate genes that encode E3 ubiquitin-protein ligase HIP1, EMBRYO-DEFECTIVE (EMB) protein, receptor-like protein kinase FERONIA (FER), kinesin-4 protein SRG1, and so on, which may be associated with the big grain mutant bg1.
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- Photothermal effect-assisted reduced graphene oxide biosensor for amplification-free detection of miRNA10
The photothermal effect-assisted reduced graphene oxide (rGO) biosensor that combines the photothermal effect of rGO with the rGO-based RI sensor for high-sensitivity detection of tumor marker miRNA-21 offers a promising approach for high-sensitivity detection of tumor marker miRNA without need for nucleic acid amplification.
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- Learning for Scale-Arbitrary Super-Resolution from Scale-Specific Networks9
This paper proposes a plug-in module for existing SR networks to perform scale-arbitrary SR, which consists of multiple scale- aware feature adaption blocks and a scale-aware upsampling layer, and introduces a Scale-aware knowledge transfer paradigm to transfer knowledge from scale-specific networks to the scale-Arbitrary network.
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- Ship detection based on medium-low resolution remote sensing data and super-resolved feature representation8
A simple but effective ship detection method called ShipSR-Det, in which both the output image and the intermediate features of the SR module are fed to the detection module, which shows superior performance on the HRSC2016, DOTA and NWPU VHR-10 datasets.
- Shipsrdet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation8
The potential benefits introduced by image SR to ship detection are explored, an end-to-end network named ShipSRDet is proposed, which can recover the missing details from the input image and achieves promising ship detection performance.
- A new computational framework for anatomically consistent 3D statistical shape analysis with clinical imaging applications8
A computational approach is presented for the quantitative comparison and statistical decomposition of sets of 3D closed genus-0 surfaces obtained from untagged medical images using a two-step surface parameterisation technique followed by the proper orthogonal decomposition method.
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- Selective transmembrane transport of Aβ protein regulated by tryptophan enantiomers6
The l-Trp channel performs effectively selectivity for the transport of Aβ protein, which would provide a new perspective for the pathological studies of Alzheimer's disease.
- Flickr1024: A Dataset for Stereo Image Super-Resolution.6
A large-scale stereo dataset named Flickr1024 is proposed that can improve the performance of stereo SR algorithms and is trained on the KITTI2015, Middlebury, and Flickr1024 datasets.
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- Learning Sparse Masks for Efficient Image Super-Resolution5
An SR network (SMSR) is developed to learn sparse masks to prune redundant computation conditioned on the input image so that redundant computation can be accurately located and skipped while maintaining comparable performance.
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- An efficient method for the fusion of light field refocused images4
This paper proposes an efficient multi-focus image fusion method based on stationary wavelet transform (SWT), which can deal with a large quantity of multi- focus images with shallow depth of fields and compares SWT-based approach with DWT- based approach on various occasions.
- Reprojection-based method for camera arrays of refocusing onto arbitrary focal surfaces4
This paper proposed a reprojetion-based method to refocus the images captured by camera arrays onto arbitrary focal surfaces, rather than only planes, using the camera imaging model and the equation of the focal surface.
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- Adaptive Spectral Denoising Network for Efficient Maneuvering Target Tracking2
This work proposes the adaptive spectral denoising network (ASDN), comprising an adaptive spectral denoising filter (ASDF) and a temporal local-pattern guided block (TLGB), and introduces large-scale maneuvering target trajectory (LASTv2), a large-scale dataset of maneuvering target trajectories characterized by diverse and complex motion patterns, specifically designed to simulate real-world adversarial scenarios with high mobility and stochastic dynamics.
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- Profiling of Biofluid Metabolites with a Kinetically Differentiated Binary Biosensing Platform2
A kinetically differentiated binary biosensing platform that is specifically responsive to NAD(P)H for profiling diverse biofluid metabolites is reported and provides a universal paradigm for high throughput profiling of disease-associated biomolecules, which offers good promise in disease diagnosis and health management.
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- COVID‐19‐associated liver injury: Adding fuel to the flame2
A review of the clinical and laboratory hepatic characteristics in COVID‐19 patients is provided, the etiology and impact of liver injury is described, and potential pathophysiological mechanisms are discussed.
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- Revisiting Subspace Disentangling for Light Field Spatial Super-Resolution1
This paper develops a simple, modular, and scalable LF spatial SR network, based on subspace disentangling, and conducts extensive experiments to quantitatively evaluate the contributions of each subspace branch, the model scaling property, and the depth-width trade-off.
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- Dual Prompt Guidance for Cross-Scene Hyperspectral Anomaly Detection–
Experimental results demonstrate that the proposed dual prompt-guided training-free method for cross-scene HAD achieves superior cross-scene detection performance to existing state-of-the-art HAD methods without additional training.
- Modulating Transformers With Explicit Degradation Information for Real-World Light Field Image Super-Resolution–
De degradation-guided Modulator is proposed, which incorporates explicit degradation information into Transformer-based LF image SR and dynamically modulates the generation of Query, Key, and Value to prevent complex degradations from misguiding the attention calculation.
- Instance Segmentation as Tracking: A New Paradigm for Multi-small-Object Tracking with Event Cameras–
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- Sparse Rational Polynomial Coefficient Estimation Method via Low-Rank Matrix Constraint–
This paper proposes a sparse RPC estimation method via low-rank matrix constraint, called LRMC-RFM, and demonstrates that the proposed method achieves better performance than existing competing methods.
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- Notice of Removal: Flexible Refocusing Method for Camera Arrays Based on Reprojection–
A flexible algorithm of refocusing is proposed for images captured by camera arrays by utilizing the parameters estimated by camera calibration, the reprojection can be used to produce images refocused on arbitrary plane.
- Biomimetic Extracellular Vesicles Embedded with Black Phosphorus for Molecular Recognition-Guided Biomineralization–
Considering the excellent behavior of the Apt-bioinspired MVs for promoting biomineralization, this strategy provides a way of designing bionic tools for studying the mechanisms of biological processes and advancing the development of medical engineering.
- Design and Implementation of Reusable Software Development Framework Based on.Net–
In this paper, a reusable software WebFrameWork based on.Net is proposed, in which some commonly used features modules are integrated in the development process of database systems to improve the efficiency of database system development.
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- On the Design of Waveform Generator–
This paper discusses the design of a new type multi-waveform generator by use of LSI circuit, which is controlled by a single chip microcomputer in order to realize the digital display.
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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