LEADER 10735nam 2200505 450 001 996464413603316 005 20231110221651.0 010 $a981-16-7189-3 035 $a(CKB)5470000001298855 035 $a(MiAaPQ)EBC6795914 035 $a(Au-PeEL)EBL6795914 035 $a(OCoLC)1281772636 035 $a(PPN)258297603 035 $a(EXLCZ)995470000001298855 100 $a20220720d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aImage and graphics technologies and applications $e16th Chinese conference on image and graphics technologies, IGTA 2021, Beijing, China, June 6-7, 2021, revised selected papers /$fedited by Yongtian Wang and Weitao Song 210 1$aSingapore :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (283 pages) 225 1 $aCommunications in Computer and Information Science ;$vv.1480 311 $a981-16-7188-5 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Organization -- Contents -- Image Processing and Enhancement Techniques -- Residual Multi-resolution Network for Hyperspectral Image Denoising -- 1 Introduction -- 2 Methodology -- 2.1 Network Architecture -- 2.2 Residual Multi-Resolution Block -- 3 Experimental Results and Analysis -- 3.1 Experimental Setup -- 3.2 Results and Analysis -- 4 Conclusion -- References -- Skin Reflectance Reconstruction Based on the Polynomial Regression Model -- 1 Introduction -- 2 Related Work -- 2.1 Human Skin Spectral -- 2.2 Polynomial Regression Model -- 3 Algorithms -- 3.1 The Xiao's Algorithm -- 3.2 The Proposed Algorithm -- 3.3 Regularization -- 4 Experiment Setup -- 4.1 Evaluation Metrics -- 4.2 Experiment Data -- 5 Result and Discussion -- 6 Conclusion -- References -- From Deep Image Decomposition to Single Depth Image Super-Resolution -- 1 Introduction -- 2 The Proposed Method -- 2.1 Depth Dual Decomposition Block -- 2.2 Depth Image Initialization Block -- 2.3 Depth Image Rebuilding Block -- 2.4 Loss Function -- 3 Experimental Results -- 3.1 Training Details -- 3.2 The Objective Quality Comparison of Different Methods -- 3.3 The Visual Quality Comparison of Different Methods -- 4 Conclusion -- References -- Classification of Solar Radio Spectrum Based on VGG16 Transfer Learning -- 1 Introduction -- 2 VGG16 and Transfer Learning -- 2.1 VGG16 Convolutional Neural Network Model -- 2.2 Transfer Learning -- 3 Spectrum Image Preprocessing and Classification Algorithm -- 3.1 Preprocessing of Solar Radio Spectrum Data -- 3.2 VGG16 Transfer Learning Algorithm -- 4 Experimental Results and Analysis -- 5 Conclusion -- References -- A Channel Attention-Based Convolutional Neural Network for Intra Chroma Prediction of H.266 -- 1 Introduction -- 2 Proposed Method -- 2.1 Neighboring Block Information Extraction Module. 327 $a2.2 Current Block Information Extraction Module -- 2.3 Feature Fusion Module -- 3 Experiment Results -- 3.1 The Robustness Analysis of Chroma Prediction Performance -- 3.2 Coding Performance -- 4 Conclusion -- References -- Biometric Identification Techniques -- A Novel Deep Residual Attention Network for Face Mosaic Removal -- 1 Introduction -- 2 The Proposed Method -- 2.1 Parallel Residual Block -- 2.2 Channel Attention -- 2.3 Pixel Attention -- 3 Experimental Results -- 3.1 Experimental Settings -- 3.2 Quantitative and Qualitative Evaluation -- 4 Conclusion -- References -- Machine Vision and 3D Reconstruction -- Pretrained Self-supervised Material Reflectance Estimation Based on a Differentiable Image-Based Renderer -- 1 Introduction -- 2 Related Work -- 3 Self-supervised Architectures -- 4 Image-Based Differentiable Renderer -- 4.1 Normal Representation -- 4.2 Ambient Light Representation -- 4.3 Material Representation -- 5 Synthetic Dataset -- 6 Loss Functions -- 7 Experiments -- 8 Conclusion -- References -- Image/Video Big Data Analysis and Understanding -- Object-Aware Attention in Few-Shot Learning -- 1 Introduction -- 2 Related Work -- 2.1 Few-Shot Learning -- 2.2 Saliency Object Detection -- 3 Method -- 3.1 Preliminaries -- 3.2 Framework -- 3.3 Object-Aware Attention Module -- 4 Experiments -- 4.1 Datasets -- 4.2 Baseline Models and Experiment Details -- 4.3 Experiment Result -- 5 Conclusion -- References -- Simultaneously Predicting Video Object Segmentation and Optical Flow Without Motion Annotations -- 1 Introduction -- 2 Methodology -- 2.1 Base Model -- 2.2 Object Flow Synthesizing -- 3 Network Implementation and Training -- 3.1 Offline Training -- 3.2 Online Training -- 4 Experimental Results -- 4.1 Dataset and Evaluation Metrics -- 4.2 Ablation Study on Video Object Segmentation -- 4.3 Segmentation Results -- 4.4 Object Flow. 327 $a4.5 Runtime Analysis -- 5 Concluding Remarks -- References -- Recognition of Bending Deformed Pipe Sections in Geological Disaster Area Based on an Ensemble Learning Model -- 1 Introduction -- 2 Feature Engineering -- 2.1 Typical Pipe Section -- 2.2 IMU Data Feature Construction -- 3 Ensemble Learning -- 3.1 Support Vector Machine -- 3.2 K-means Clustering -- 3.3 Ensemble Learning Based on Voting Method -- 3.4 Analysis of Results -- 4 Conclusion -- References -- Memory Bank Clustering for Self-supervised Contrastive Learning -- 1 Introduction -- 2 Related Work -- 2.1 Self Supervised Contrastive Learning -- 2.2 Memory Bank Based Method -- 3 Method -- 3.1 Contrastive Learning with Memory Bank Clustering -- 3.2 Training with Dynamic Memory Bank -- 3.3 Contrastive Loss with Dynamic Memory Bank -- 4 Experiment -- 4.1 Experiment Details -- 4.2 Experimental Results -- 5 Conclusion -- References -- Robust Visual Question Answering Based on Counterfactual Samples and Relationship Perception -- 1 Introduction -- 2 Related Work -- 2.1 Visual Question Answering -- 2.2 Counterfactual Sample Synthesis Mechanism for VQA -- 2.3 Relationship Perception in VQA -- 3 Method -- 3.1 Relationship Perception Network -- 3.2 Counterfactual Sample Generation Mechanism -- 3.3 Loss Functions -- 4 Experiment -- 4.1 Dataset -- 4.2 Parameter Setting -- 4.3 Performance on the VQA-CP v2 Dataset -- 4.4 Performance on the VQA V2 Dataset -- 4.5 Ablation Experiment of CSRP Model -- 5 Conclusion -- References -- Prototype Generation Based Shift Graph Convolutional Network for Semi-supervised Anomaly Detection -- 1 Introduction -- 2 Related Work -- 2.1 Video Anomaly Detection -- 2.2 Graph Convolutional Networks -- 2.3 Prototype Generation Module -- 3 Method -- 3.1 Architecture Overview -- 3.2 Feature Extraction Module -- 3.3 Prototype Generation Module -- 3.4 VAD Objective Functions. 327 $a4 Experiments -- 4.1 Experiments on ShanghaiTech -- 4.2 Ablation Study -- 5 Conclusion -- References -- Computer Graphics -- A New Image Super-Resolution Reconstruction Algorithm Based on Hybrid Diffusion Model -- 1 Introduction -- 2 Related Work -- 2.1 Characteristics of Fractional Differential Operators -- 2.2 Fractional Anisotropic Diffusion Model -- 3 Model Algorithm and Design -- 3.1 Proposal of Mixed Diffusion Model -- 3.2 Realization of Adaptive Diffusion Function -- 3.3 Numerical Calculation of the Algorithm -- 4 Experiment and Analysis -- 5 Conclusion -- References -- Research on Global Contrast Calculation Considering Color Differences -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Traditional Method of Global Contrast -- 3.2 Global Contrast Calculation Considering Color Differences -- 4 Experimental Results -- 5 Conclusion -- References -- Virtual Reality and Human-Computer Interaction -- Research on Key Technologies and Function Analysis of Live Interactive Classroom in AI+ Era -- 1 Introduction -- 2 Advantages and Disadvantages of Webcast Classroom -- 2.1 Advantages of Webcast Class -- 2.2 Disadvantages of Webcast Class -- 3 AI Plus Key Technology of Synchronous Live Broadcast in Class -- 3.1 Face Recognition Technology -- 3.2 Human Behavior and Expression Analysis -- 3.3 Natural Language Processing -- 3.4 Knowledge Graph and Expert Systems -- 4 The Main Functions of Open Education AI Live Class -- 4.1 Basic Framework of the Platform -- 4.2 Introduction of AI Live-Streaming Classroom Functions -- 5 Conclusion -- References -- Applications of Image and Graphics -- BrainSeg R-CNN for Brain Tumor Segmentation -- 1 Introduction -- 2 Method -- 2.1 Mask R-CNN -- 2.2 BrainSeg R-CNN -- 3 Experiments -- 3.1 Dataset and Settings -- 3.2 Compared Experiments Using Slices with Tumors -- 3.3 Compared Experiments Using Whole Brain Image. 327 $a4 Conclusion -- References -- A Real-Time Tracking Method for Satellite Video Based on Long-Term Tracking Framework -- 1 Introduction -- 2 Method Framework -- 2.1 Feature Extraction -- 2.2 Re-detection Mechanism -- 2.3 PCA Based Dimensionality Reduction -- 3 Experimental Results and Analysis -- 4 Conclusion -- References -- Fourier Series Fitting of Space Object Orbit Data -- 1 Introduction -- 2 Related Works -- 2.1 TLE Orbit Data -- 2.2 Orbit Elements -- 3 Data Fitting -- 3.1 Commonly Used Fitting Algorithms -- 3.2 Fourier Series Fitting -- 4 Experiment and Analysis -- 4.1 Classification Selection of Experimental Samples -- 4.2 Data Pre-processing -- 4.3 Evaluation Criteria of Fitting Results -- 4.4 Data Fitting -- 4.5 Predicting Results -- 5 Conclusion -- References -- Mapping Methods in Teleoperation of the Mars Rover -- 1 Introduction -- 2 Mars Rover Teleoperation Control Mode -- 3 Multi-scale Mapping Mode Based on Multi-source Data -- 3.1 Large Area Mapping Using Orbit Images Based on the Two-Stage Method -- 3.2 Landing Site Mapping Using Descent Sequence Images -- 3.3 3D Terrain Reconstruction Based on Image Fusion -- 3.4 Wide Baseline Mapping Using Multi-site Images -- 4 Conclusions -- References -- Other Research Works and Surveys Related to the Applications of Image and Graphics Technology -- A Regularized Limited-Angle CT Reconstruction Model Based on Sparse Multi-level Information Groups of the Images -- 1 Introduction -- 2 Analysis of Group Sparsity Model -- 3 The Proposed Model -- 4 Algorithms -- 5 Numerical Experiments -- 6 Conclusions and Prospects -- References -- Author Index. 410 0$aCommunications in Computer and Information Science 606 $aSemantics 615 0$aSemantics. 676 $a636.005 702 $aWang$b Yongtian 702 $aSong$b Weitao 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464413603316 996 $aImage and Graphics Technologies and Applications$92568128 997 $aUNISA LEADER 03239nam 22006852 450 001 9910779439603321 005 20160318120116.0 010 $a1-139-61118-6 010 $a1-107-23793-9 010 $a1-139-60936-X 010 $a1-139-61304-9 010 $a1-139-61676-5 010 $a1-139-42440-8 010 $a1-139-62606-X 010 $a1-283-87069-X 010 $a1-139-62234-X 035 $a(CKB)2550000000709574 035 $a(EBL)1099947 035 $a(OCoLC)828302639 035 $a(SSID)ssj0000783337 035 $a(PQKBManifestationID)11435678 035 $a(PQKBTitleCode)TC0000783337 035 $a(PQKBWorkID)10771206 035 $a(PQKB)11196160 035 $a(UkCbUP)CR9781139424400 035 $a(MiAaPQ)EBC1099947 035 $a(Au-PeEL)EBL1099947 035 $a(CaPaEBR)ebr10634035 035 $a(CaONFJC)MIL418319 035 $a(PPN)261276646 035 $a(EXLCZ)992550000000709574 100 $a20120424d2013|||| uy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aGeneralized vectorization, cross-products, and matrix calculus /$fDarrell A. Turkington$b[electronic resource] 210 1$aCambridge :$cCambridge University Press,$d2013. 215 $a1 online resource (xi, 267 pages) $cdigital, PDF file(s) 300 $aTitle from publisher's bibliographic system (viewed on 24 Feb 2016). 311 $a1-107-44872-7 311 $a1-107-03200-8 320 $aIncludes bibliographical references and index. 327 $a1. Mathematical prerequisites -- 2. Zero-one matrices -- 3. Elimination and duplication matrices -- 4. Matrix calculus -- 5. New matrix calculus results -- 6. Applications. 330 $aThis book presents the reader with new operators and matrices that arise in the area of matrix calculus. The properties of these mathematical concepts are investigated and linked with zero-one matrices such as the commutation matrix. Elimination and duplication matrices are revisited and partitioned into submatrices. Studying the properties of these submatrices facilitates achieving new results for the original matrices themselves. Different concepts of matrix derivatives are presented and transformation principles linking these concepts are obtained. One of these concepts is used to derive new matrix calculus results, some involving the new operators and others the derivatives of the operators themselves. The last chapter contains applications of matrix calculus, including optimization, differentiation of log-likelihood functions, iterative interpretations of maximum likelihood estimators and a Lagrangian multiplier test for endogeneity. 517 3 $aGeneralized Vectorization, Cross-Products, & Matrix Calculus 606 $aMatrices 606 $aVector analysis 615 0$aMatrices. 615 0$aVector analysis. 676 $a515/.63 686 $aBUS021000$2bisacsh 700 $aTurkington$b Darrell A.$0266648 801 0$bUkCbUP 801 1$bUkCbUP 906 $aBOOK 912 $a9910779439603321 996 $aGeneralized vectorization, cross-products, and matrix calculus$93817265 997 $aUNINA