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- 1,938
- Richer Convolutional Features for Edge Detection1,240
RCF encapsulates all convolutional features into more discriminative representation, which makes good usage of rich feature hierarchies, and is amenable to training via backpropagation, and achieves state-of-the-art performance on several available datasets.
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- HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interaction435
Three benchmarking tasks to pro-mote category-level HOI from 4D visual signals are established including semantic segmentation of 4D dynamic point cloud se-quences, category- level object pose tracking, and egocen-tric action segmentation with diverse interaction targets.
- MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation352
A multi-stage architecture for the temporal action segmentation task that overcomes the limitations of the previous approaches and achieves state-of-the-art results on three datasets: 50Salads, Georgia Tech Egocentric Activities (GTEA), and the Breakfast dataset.
- P2T: Pyramid Pooling Transformer for Scene Understanding321
This paper proposes to adapt pyramid pooling to Multi-Head Self-Attention (MHSA) in the vision transformer, simultaneously reducing the sequence length and capturing powerful contextual features, in a universal vision transformer backbone, dubbed Pyramid Pooling Transformer (P2T).
- EDN: Salient Object Detection via Extremely-Downsampled Network284
This work introduces an Extremely-Downsampled Network (EDN), which employs an extreme downsampling technique to effectively learn a global view of the whole image, leading to accurate salient object localization and construct the Scale-Correlated Pyramid Convolution (SCPC) to accomplish better multi-level feature fusion.
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- Pyramid Constrained Self-Attention Network for Fast Video Salient Object Detection184
A Constrained Self-Attention (CSA) operation to capture motion cues, based on the prior that objects always move in a continuous trajectory is designed, which outperforms previous state-of-the-art methods in both accuracy and speed.
- MobileSal: Extremely Efficient RGB-D Salient Object Detection176
This article proposes an implicit depth restoration (IDR) technique to strengthen the mobile networks’ feature representation capability for RGB-D SOD, and proposes compact pyramid refinement (CPR) for efficient multi-level feature aggregation to derive salient objects with clear boundaries.
- MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation166
MiniSeg, a lightweight deep learning model for efficient COVID-19 segmentation, has several significant strengths: i) it only has 83K parameters and is thus not easy to overfit; ii) it has high computational efficiency and is therefore convenient for practical deployment; and iii) it can be fast retrained by other users using their private CO VID-19 data for further improving performance.
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- Semantic Edge Detection with Diverse Deep Supervision113
A novel fully convolutional neural network using diverse deep supervision within a multi-task framework where bottom layers aim at generating category-agnostic edges, while top layers are responsible for the detection of category-aware semantic edges is proposed.
- DNA: Deeply Supervised Nonlinear Aggregation for Salient Object Detection113
The proposed saliency detector, a modified U-Net architecture with DNA, performs favorably against state-of-the-art methods on various datasets and evaluation metrics without bells and whistles and can successfully break through the bottleneck of the current linear approaches.
- Multi-Scale Interaction for Real-Time LiDAR Data Segmentation on an Embedded Platform105
The proposed Multi-scale Interaction Network (MINet) uses multiple paths with different scales and balances the computational resources between the scales and outperforms point-based, image- based, and projection-based methods in terms of accuracy, number of parameters, and runtime.
- Vision Transformers with Hierarchical Attention103
This paper proposes hierarchical MHSA (H-MHSA), a novel approach that computes sell-attention in a hierarchical fashion, and builds a family of hierarchical-attention-based transformer networks, namely HAT-Net, which provides a new perspective for vision transformers.
- Efficient semi-supervised feature selection with noise insensitive trace ratio criterion101
This paper proposes a noise insensitive trace ratio criterion for feature selection with a re-scale preprocessing and proposes an efficient semi-supervised feature selection algorithm to select relevant features using both labeled and unlabeled data.
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- Stereoscopic image quality assessment method based on binocular combination saliency model93
An effective method to evaluate the quality of stereoscopic images that are afflicted by symmetric distortions is proposed and a new 3D saliency map is developed, which not only greatly reduces the computational complexity by avoiding calculation of the depth information, but also assigns appropriate weights to the image contents.
- Automated detection of cardiovascular disease by electrocardiogram signal analysis: a deep learning system81
The proposed CNN model could help reduce misdiagnosis and missed diagnosis in primary care settings and also improve efficiency and save manpower cost for large general hospitals.
- A Hand Gesture Recognition Method Based on Multi-Feature Fusion and Template Matching72
Experiments show that the proposed hand gesture recognition method based on multi-feature fusion and template matching is effective for extracting features of different hand gestures and real-time recognition of ten kinds of hand gestures.
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- DOTS: Decoupling Operation and Topology in Differentiable Architecture Search60
The proposed Decouple the Operation and Topology Search (DOTS), which decouples the topology representation from operation weights and makes an explicit topology search, and is an effective solution for differentiable NAS.
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- Advances in signal amplification strategies for electrochemical biosensing60
This review focuses on the advances during the last decade in the development and application of signal amplified EC, photoelectrochemical and electrochemiluminescence biosensing, using functional nanomaterials, enzyme catalysis and biological reactions.
- Acetylcholinesterase Activity Monitoring and Natural Anti-neurological Disease Drug Screening via Rational Design of Deep Eutectic Solvents and CeO2-Co(OH)2 Nanosheets58
Based on their excellent oxidase-like activity, the CeO2-Co(OH)2 nanosheets have been successfully applied for highly sensitive and selective detection of AChE with a linear range of 0.2-20 mU/mL and can also be used for inhibitor screening.
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- Boosting Salient Object Detection With Transformer-Based Asymmetric Bilateral U-Net56
A transformer-based Asymmetric Bilateral U-Net, which enables AbiU-Net to learn complementary global and local representations, taking advantage of the natural merits of transformers and CNNs, respectively.
- Ordered or Orderless: A Revisit for Video Based Person Re-Identification52
This paper presents a simple yet surprisingly powerful approach for VPRe-id, where it is shown that the common practice of employing recurrent neural networks to aggregate temporal-spatial features may not be optimal and provides an error bound that sheds light upon how could the authors improve VP re-identification.
- Rethinking Few-shot 3D Point Cloud Semantic Segmentation50
This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS), with a focus on two significant is-sues in the state-of-the-art: foreground leakage and sparse point distribution, and proposes a novel FS-PCS model based on correlation optimization, referred to as Correlation Optimization Segmentation (COSeg).
- Learning Local and Global Temporal Contexts for Video Semantic Segmentation47
A Coarse-to-Fine Feature Mining (CFFM) technique to learn a unified presentation of LTC, and a CFFM++ by additionally learning GTC from the whole video to further exploit more temporal contexts.
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- Sequential Optimization for Efficient High-Quality Object Proposal Generation44
A novel object proposal algorithm, BING++, is proposed, which inherits the virtue of good computational efficiency of BING but significantly improves its proposal localization quality.
- Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-Resolution43
This study finds that transformer structures are more adept at capturing low-frequency information, but have limited capacity in constructing high-frequency representations when compared to their convolutional counterparts, and introduces a frequency-guided post-training quantization (PTQ) method aimed at enhancing CRAFT's efficiency.
- Discriminative unsupervised dimensionality reduction40
This paper proposes a novel graph embedding method that simultaneously conduct dimensionality reduction along with graph construction by assigning adaptive and optimal neighbors according to the projected local distances and concludes that the learned graph is optimal fordimensionality reduction.
- Revisiting Computer-Aided Tuberculosis Diagnosis39
A large-scale dataset, namely the Tuberculosis X-ray (TBX11 K) dataset, is established, which contains 11 200 chest X-ray (CXR) images with corresponding bounding box annotations for TB areas and a strong baseline, SymFormer, is proposed, for simultaneous CXR image classification and TB infection area detection.
- CubemapSLAM: A Piecewise-Pinhole Monocular Fisheye SLAM System32
This work proposes a novel SLAM system with the cubemap model that utilizes the full FoV without introducing distortion from the fisheye lens, which greatly benefits the feature matching pipeline.
- Mobile-Seed: Joint Semantic Segmentation and Boundary Detection for Mobile Robots31
This work introduces Mobile-Seed, a lightweight, dual-task framework tailored for simultaneous semantic segmentation and boundary detection, featuring a two-stream encoder, an active fusion decoder (AFD), and a dual-task regularization approach.
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- Rethinking Global Context in Crowd Counting27
Extensive experiments on various datasets, including ShanghaiTech, UCF-QNRF, JHU-CROWD++ and NWPU, demonstrate that the proposed context extraction techniques can significantly improve the performance over the baselines.
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- MD-UNet: a medical image segmentation network based on mixed depthwise convolution25
A U-shaped medical image segmentation network based on a Mixed depthwise convolution residual module (MDRM) built with a Mixed depthwise convolution attention block (MDAB) that captures both local and global dependencies in the image to mitigate the effects of intra-class differences.
- BING++: A Fast High Quality Object Proposal Generator at 100fps21
A novel object proposal algorithm is proposed which inherits the good computational efficiency of BING but significantly improves its proposal localization quality and also recursively improves BING++'s proposals by exploiting the fact that edges in images are typically associated with object boundaries.
- Motion boundary emphasised optical flow method for human action recognition20
The results showed the importance of accurate optical flow plays in human action recognition, an aspect which has been seldom addressed, and showed that if some measure of the global behaviours of motion is incorporated, the generalisation performance is often improved by 1–2%.
- Automatic Feature Exploration and an Application in Defect Prediction20
A new model, named neural forest (NF), is proposed, which uses the deep neural network and decision forest to build a holistic system for the automatic exploration of powerful feature representations that are used for the following classification.
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- Exploiting Temporal State Space Sharing for Video Semantic Segmentation17
A Temporal Video State Space Sharing (TV3S) architecture to leverage Mamba state space models for temporal feature sharing, which features a selective gating mechanism that efficiently propagates relevant information across video frames, eliminating the need for a memory-heavy feature pool.
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- Refinedbox: Refining for fewer and high-quality object proposals17
A computationally lightweight neural network is designed to reduce the number of proposals in object proposal generation, and can achieve state-of-the-art performance with a few proposals compared with some well-known proposal generation methods.
- Defect automatic detection for tire X-ray images using inverse transformation of principal component residual17
An image reconstruction algorithm using inverse transformation of principal component residual to automatically detect the tire defects in its X-ray image using none-dominant textures of tires that is considered as abnormal or defect textures is developed.
- Intelligent MEMS Sensor Based on an Oxidized Medium-Entropy Alloy (FeCoNi) for H2 and CO Recognition16
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- RGB‐D Human Action Recognition of Deep Feature Enhancement and Fusion Using Two‐Stream ConvNet15
This paper makes full use of video and deep skeleton data and proposes an RGB-D action recognition based two-stream network (SV-GCN), which can be described as a two- stream architecture that works with two different data.
- A simple saliency detection approach via automatic top-down feature fusion15
An Automatic Top-Down Fusion (ATDF) method, in which the global information at the top sides are flowed into bottom sides to guide the learning of low layers, is proposed, which opens a new path for saliency detection.
- Transfer Learning via Artificial Intelligence for Guiding Implant Placement in the Posterior Mandible: an in vitro Study12
It can be concluded that theAI system has the capacity of deep learning and as more characteristic annotators be involved in the algorithm, the AI system can figure out the anatomy of the object region better, then generate the ideal implant plan via deep learning algorithm.
- TCN-MBMAResNet: a novel fault diagnosis method for small marine rolling bearings based on time convolutional neural network in tandem with multi-branch residual network11
TCN is introduced to capture dependencies in long time series and optimize the feature distribution of raw data to address the challenges in extracting fault features from centrifugal pump bearings in ship water replenishment systems and the low accuracy of fault identification caused by unbalanced data samples.
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- Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences10
This paper presents tracking algorithm of multiple pedestrians based on particle filters in video sequences that improves the tracking performance and has better tracking results.
- Pedestrian detection algorithm based on video sequences and laser point cloud10
Experimental verification and analysis in video sequences demonstrate that fusion of two data improves the performance of pedestrian detection and has better detection results.
- Research on fault diagnosis method of turbocharger rotor based on Hu-SVM-RFE9
Hu-SVM-RFE feature screening method combined with PNN fault diagnosis technology has high accuracy and efficiency, which is of great significance for online fault identification of the supercharger rotor.
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- Ret3D: Rethinking Object Relations for Efficient 3D Object Detection in Driving Scenes8
This work introduces a simple, efficient, and effective two-stage detector, termed as Ret3D, which utilization of novel intra-frame and inter-frame relation modules to capture the spatial and temporal relations accordingly.
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- Pharmacokinetic Properties and Therapeutic Effectiveness of Remimazolam in ICU Patients With Mechanical Ventilation: A Preliminary Study6
The pharmacokinetic study indicates that remimazolam is effective and safe for ICU patients on mechanical ventilation, with a 24‐h infusion demonstrating rapid clarence and a clear dose‐effect relationship.
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- A Novel Method for Temporal Action Localization and Recognition in Untrimmed Video Based on Time Series Segmentation6
A method with temporal boundary regression based on time series segmentation, which can generate proposals with flexible temporal duration and which can effectively improve the classification accuracy is proposed.
- Multi-views Action Recognition on Deep Learning and K-SVD6
This paper extracts the feature maps from the different views by convolutional neural networks and long short term memory, and the extracted feature maps are the multi-views high-level features with semantic information, and uses the K-SVD sparse algorithm to get dictionaries corresponding to each views.
- Video Object Segmentation of Still Background6
Experiments on the platform of TMS320C6711 IDK(Imaging Developer's Kit) of Texas Instruments implies that this algorithm can segment video object and meet needs of applications of MPEG-4.
- Moving object properties-based video saliency detection5
The proposed video saliency detection approach by constructing the moving object properties, meaning that motion is in concurrence with a general object for detected regions, outperforming the state-of-the-art methods.
- Single Image Dehazing Based on Weighted Variational Regularized Model5
The dark channel prior (DCP) and luminance model are used to estimate the coarse transmission in this work, which can deal with the problem of transmission estimation in the sky area and can preserve the important image details and suppress image noise in the dehazing process.
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- A New Link Scheduling Algorithm for 60 GHz-WPAN Communication System5
An average time slot multiplexing allocation (ATSMA) algorithm based on space/time division multiple access (STDMA) solution is proposed, which allows concurrent transmission in a single time slot and demonstrated that the capacity gain is obvious using ATSMA algorithm, no matter whether under omnidirectional antenna or under directional antenna.
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- Localizing discriminative regions for fine-grained visual recognition: One could be better than many4
- LSTM-based Flow Prediction4
The proposed method employs an LSTM algorithm enhanced through multivariate tuning that refines the conventional LSTM by transforming time series data into supervised learning sequences, tailored to the distinctive features of industrial data.
- Nonlinear Grey Bernoulli model NGBM (1, 1)'s parameter optimisation method and model application4
This paper builds the NGBM (1, 1) models of China's GDP and energy consumption with three improvement methods and offers good approaches for the in-depth study on nonlinear grey Bernoulli model, enrich the method system of grey modelling.
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- Projected-point-based Segmentation: A New Paradigm for LiDAR Point Cloud Segmentation4
This work proposes a new paradigm, namely projected-point-based methods, to transform point- based methods to a suitable form for LiDAR point cloud segmentation by utilizing the characteristics of LiDar point clouds.
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- A Novel Method for Feature Extraction and Automatic Recognition of Tire Defects Using Independent Component Analysis4
A new approach using Independent Component Analysis (ICA) and Topographic Independent component Analysis (TICA) reconstruction algorithm to extract the features of tire defects and apply automatic recognition of tire defect images.
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- Salient object detection based on hierarchical segmentation and objectness-guided3
This paper proposes a new bottom-up method to better highlight the integral salient object region by exploiting the co-occurrence of saliency and objectness properties and demonstrates that the proposed method can efficiently remove the interference of non-salient objects and complex background while preserving more salient object regions.
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- Approach of Car License Plate Extraction Based on Math Morphology3
A new approach of extracting carlicense plate from car images based on morphology is presented, based on the information of width and height of car license plate, height of character and space between charac- ters of the car licenses plate, and some new structural elements for morphological operations are designed and used to detect the edge image of car License plate.
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- Modeling and Analysis of Ecological Urban Landscape Pattern Evolution Based on Multisource Remote Sensing Data2
The experimental results show that, from 2005 to 2020, the development level of urbanization process is higher and higher and the area of building land patches is increasing, which reduces the fragmentation ofBuilding land patches, but the landscape of cultivated land and green space is less and less, and the distribution of patches also causes uneven phenomenon, which leads to the gradual decline of ecological urban landscape diversity.
- No-reference stereoscopic images quality assessment method based on monocular superpixel visual features and binocular visual features2
A novel quality assessment model based on the superpixel index and biological binocular mechanisms is proposed that has a more reliable performance than earlier models in terms of prediction accuracy and generalizability.
- Object Detection Method Based on Three-dimension Information Extraction of Laser Point Cloud2
Experimental results show that object detection method based on 3D information extraction of laser point cloud improves the detection performance, and new research ideas and theoretical basis for the improvement of object detection performance are provided.
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- Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality2
An improved stereo matching network, SLED-Net, is explored, in which a Single Long Encoder-Decoder is proposed to replace the stacked hourglass network in PSM-Net for better contextual information learning.
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- Real-time Stature Measurement Algorithm Based on Monocular Vision Technique2
A new method for stature measurement which is applied to the driver physical examination system is introduced and it has reduced the operation complexity and hardware complication by integrating the stature measurement module with the others in the driverPhysical examination system.
- An Approach Based on Morphology for Car License Plate Extraction2
A new method based on morphology for license plate extraction from car images, which is combined width and height of car license plate, height of character, and space between characters of the carlicense plate is presented.
- Runtime Analysis of Evolutionary NAS for Multiclass Classification1
It is proved that the algorithm using both mutations can find the optimum with the expected runtime upper bound of $O(rM\ln{rM})$ and lower bound of $\Omega(rM\ln{M})$.
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- Design and Implementation of Web-based Database Virtual Experiment Platform1
A lightweight web-based database virtual experiment platform is constructed that can effectively solve the problems of difficult implementation and uncertain experimental effects in experimental sections under the blended learning mode of database courses, effectively ensuring the quality of online teaching for such courses.
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- Personalized Fuzzy Text Search Using Interest Prediction and Word Vectorization.1
A novel text search algorithm is proposed using a inverse filtering mechanism that is very efficient for label based item search and the Bayesian network is adopted to implement the user interest prediction for an improved personalized search.
- A New Research on Contrast Sensitivity Function Based on Three-Dimensional Space1
The proposed \(\theta -CSF\) model of three-dimensional space can well reflects human visual contrast sensitivity characteristics in 3D space and has significant effect on three- dimensional image processing.
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- Research on Forecasting the State of Driver Based on Chaos Theory1
Considering ‘The state of car is the outside and mechanized expression of driver character’, the HRV sets of driver are input and a forecasting network on the state of driver is established, and a BP algorithm combing with chaos optimize algorithm is used in the network.
- Research and application of digital image processing technique in cobalt-60 based container inspection system1
This paper introduces an approach to generate two-view images for comparison by means of image data acquisition, a method to reconstruct 3D reviewing, and processing technology with a special image correction algorithm that greatly improves image quality of Cobalt-60 based inspection system compared with ordinary image processing methods.
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- Performance Optimization and Simulation Analysis of the Railway Communication Network Route Search1
It is proposed the architecture of Railway Communication Business Support System (RCBSS), and the application of Dijkstra algorithm on the auto routing and an improved scheme of route search based on the dynamic weight of load balancing is presented.
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- Robust and Sparse PCA for High‐Dimensional Data via Huber Loss and Non‐Convex Regularization–
An iterative procedure based on the local linear approximation is developed for estimating the sparse PC loadings and shows that the proposed approach provides more accurate PC estimates than the existing PCA approaches in the presence of rowwise and/or cellwise data contamination.
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- Integration Strategies of American Voice Singing in Singing and Vocal Teaching Based on Multiscale Feature Fusion–
The results showed that the more frames in the input vector, the more correct the model was, 89.32 ± 0.21 for 20 frames, increasing to 90.05 ± 1.32 for 40 frames.
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- Global and Compact Video Context Embedding for Video Semantic Segmentation–
This paper attempts to bridge the gap by learning global video context for VSS by embedding the learned global and compact video context into the features of the target video frame to improve the distinguishability.
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- Characterization of Immediate Pressing Tactics in Soccer in the Age of Artificial Intelligence–
The results show that the soccer team has the greatest success rate of practicing immediate pressing tactics in 3s-4s, and the success rates of applying immediate press tactics after 4s is significantly lower.
- A prior-guided face image super-resolution network based on attention mechanism–
The proposed method introduces an attentional multi-scale feature fusion block, which aims to improve the representation power of the neural network by emphasizing the important feature maps and suppressing the unimportant ones.
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- Application of SOM, BP Neural Network in Physical Health Assessment of Students–
Analysis of the results shows that the BP neural network can evaluate the physical health of the physical test results and show the quality of the students’ physical quality.
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- Behavior Recognition Based on Complex Linear Dynamic Systems–
This paper proposes to model the motion dynamics with complex linear dynamical systems (CLDS) and use the model parameters as motion descriptors and the KNN classifier is used to classify it.
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- Procedure-oriented University Digital Admissions System under Big Data Environment–
The use of big data is proposed to collect admission work data in each link through information system, and real-time generate statistical analysis of information, which will provide a scientific basis for decision makers.
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- Design and Implementation of Virtual Experiment System Based on Universal Design–
A kind of virtual-experiment system based on a universal design concept aimed at achieving the fast development of virtual experiments is explored, which provides a reference base for the design and development of the Internet and information products and services.
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- Pedestrians Crowd Segmentation Based on Bayesian Formulation–
Experiments result that using the PETS 2009 video database show that this algorithm can effectively and accurately detect the pedestrian whose occlusion is less half and the part of severely blocked pedestrians can also be identification.
- Trustworthiness Measure Platform of Intelligent Subway Information System–
A measurement model is developed that provides a new method for measuring the software trustworthiness and a platform used to measure the softwareTrustworthiness of the information system.
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- PROOF-OF-CONCEPT OF AN AUGMENTED REALITY APPLICATION IN DEVELOPMENTAL MATHEMATICS–
A new technological method, Augmented Reality Algebra, for developmental mathematics recitation, which relies on an interactive presentation of material via a simulated augmented reality environment and shows significant improvement in students who learn and practice the same mathematics with more traditional approaches.
- An Efficient Hybrid Beamforming for Uplink Transmissions of 60GHz Millimeter-Wave Communications–
The results show that this new scheme can significantly enhance the SINR performance of the received signal in access point and further validates the effectiveness of this presented hybrid beam forming algorithm.
- Design and Implementation of Panoramic Video Surveillance System Based on OMAP4460–
This paper profoundly analyze and discuss the embedded panoramic video surveillance system mainly from the hardware platform structures, the design of the peripheral circuit and the panorama function implement.
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- Shadow Suppression Based on Adaptive Gaussian Mixture Model–
The experimental result showed that this method can effectively solve the shadow and have good real-time performance and robustness.
- Spectral sculpting for OFDM-based cognitive radio systems by SVD precoding scheme–
To suppress the interference to Licensed Users (LUs) in orthogonal frequency division multiplexing (OFDM)-based Cognitive Radios (CR) systems, a novel spectral precoding scheme is proposed using the singular value decomposition (SVD) algorithm.
- Wavelet de-noising of strain estimates in elastography at high overlap–
A wavelet shrinkage de-noising in strain estimates to reduce the worm artifacts at high overlap and improve the performance indices of elastogram while maintaining the high axial resolution is presented.
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- Research on Electricity Cost Self-service Model Based on the Smart Client Architecture–
The operational feedback shows that the self-service model integrating Web services based the smart client architecture is manifested with favorable feasibility and wide application prospect in reducing maintenance cost and improving work quality.
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- Approach for Color Image Edge Detection Using Modified PCNN–
The main idea is to segment input color image with PCNN parameters determined by both spatial and gray level characteristics of the image initially and then obtain the edge information of color image using modified PCNN.
- An Applying of Porting μC/OS-IIto ARM7–
The process of porting and the method of testing have been discussed, a porting has been implemented in UP-TECH44B0 evaluation board, and the system runs steadily.
- Application of atraumatic restorative treatment–
The atraumatic restorative treatment (ART) is a minimally invasive method at low cost, simple and convenient and has a prominent effect on preventing and controlling early caries.
- CBFrag-Cubing: An Algorithm of High-Dimensional Data Cubing Based on Compressed Bitmap–
A partition-based CBFrag-Cubing algorithm is proposed, which uses Com- pressed bitmap index to optimize the storage of cube, and reduces the computing time.
- Algorithms for Minimum Distances Aggregation Query in Spatial Databases–
A performance study based on extensive experiments shows that threshold algorithm outperforms nearest-neighbor-based method in spatial databases and is presented for the data sets stored in the R-tree family.
- A Three-Dimension Expression of Vague Sets and a Group of Distance Measures between Them–
A three-dimension expression of Vague set membership degrees is proposed and a inequality is proved and a group of distance measures between Vague sets (values) are given.
- Methods of Maintaining External Consistency for Real-Time Data–
It is shown that the method L/S could provide expected results under several limited environments or a valid result in general, and experimental results demonstrate its efficiency.
- Analysis and Solution of Document Retrieval Course Teaching in Shandong Province–
The conditions and problems now existing in document retrieval course teaching are pointed out, and items for attention macroscopicly are suggested.
- Data Organization and Effectiveness Analysis in a Data Warehouse–
The causes of the stale data and ineffective data in a data warehouse are explained and a solution is put forward to solve the problem.
- Motion Parameters Estimation in Facial Sequence–
The key works to improve the accuracy of motion parameter estimation are the selecting of some proper feature points and the building of an exactly 3D wire frame corresponding to specified face.
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 2026-10-12. 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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