| Description |
1 online resource (xiv, 521 pages) : illustrations (chiefly color) |
| Series |
Lecture notes in computer science, 1611-3349 ; 14427 |
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Lecture notes in computer science ; 14427. 1611-3349
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| Contents |
Intro -- Preface -- Organization -- Contents - Part III -- Machine Learning -- Loss Filtering Factor for Crowd Counting -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Background and Motivation -- 3.2 Loss Filtering Factor -- 4 Experiments -- 4.1 Evaluation Metrics -- 4.2 Datasets -- 4.3 Neural Network Model -- 4.4 Experimental Evaluations -- 4.5 Key Issues and Discussion -- 5 Conclusions and Future Work -- References -- Classifier Decoupled Training for Black-Box Unsupervised Domain Adaptation -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Problem Definition |
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3.2 Overall Framework -- 3.3 Classifier Decoupled Training (CDT) -- 3.4 ETP-Entropy Sampling -- 4 Experiment -- 4.1 Setup -- 4.2 Performance Comparison -- 4.3 Analysis -- 5 Conclusion -- References -- Unsupervised Concept Drift Detection via Imbalanced Cluster Discriminator Learning -- 1 Introduction -- 2 Related Works -- 2.1 Concept Drift Detection -- 2.2 Imbalance Data Clustering -- 3 Propose Method -- 3.1 Imbalanced Distribution Learning -- 3.2 Multi-cluster Descriptor Training -- 3.3 Concept Drift Detection Based on MCD -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Comparative Results |
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4.3 Ablation Study -- 4.4 Study on Imbalance Rate and Drift Severity -- 5 Conclusion -- References -- Unsupervised Domain Adaptation for Optical Flow Estimation -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Overview -- 3.2 Domain Adaptive Autoencoder -- 3.3 Incorporating with RAFT -- 3.4 Overall Objective -- 3.5 Network Architecture -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experiment Results -- 4.3 Ablation Study -- 5 Conclusion -- References -- Continuous Exploration via Multiple Perspectives in Sparse Reward Environment -- 1 Introduction -- 2 Related Works -- 3 Method |
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3.1 Continuous Exploration via Multiple Perspectives -- 3.2 Global Reward Model -- 3.3 Local Reward Model -- 4 Experiment -- 4.1 Comparison Algorithms and Evaluation Metrics -- 4.2 Network Architectures and Hyperparameters -- 4.3 Experimental Results -- 5 Conclusion -- References -- Network Transplanting for the Functionally Modular Architecture -- 1 Introduction -- 2 Related Work -- 3 Network Transplanting -- 3.1 Space-Projection Problem of Standard Distillation and Jacobian Distillation -- 3.2 Solution: Learning with Back-Distillation -- 4 Experiments -- 4.1 Implementation Details |
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4.2 Experimental Results and Analysis -- 5 Conclusion -- References -- TiAM-GAN: Titanium Alloy Microstructure Image Generation Network -- 1 Introduction -- 2 Related Work -- 2.1 Image Generation -- 2.2 Mixture Density Network -- 3 Method -- 3.1 Framework -- 3.2 Feature-Fusion CcGAN -- 3.3 Feature-Extraction-Mapping GAN -- 4 Experiments -- 4.1 Dataset -- 4.2 Metric -- 4.3 Comparison Experiment -- 4.4 Ablation Experiment -- 5 Conclusion -- References -- A Robust Detection and Correction Framework for GNN-Based Vertical Federated Learning -- 1 Introduction -- 2 Related Works |
| Summary |
The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13⁰́₃15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. |
| Notes |
Selected conference proceedings |
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Includes author index |
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Online resource; title from PDF title page (SpringerLink, viewed January 2, 2024) |
| Subject |
Computer vision -- Congresses
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Pattern recognition systems -- Congresses
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| Genre/Form |
Electronic books
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proceedings (reports)
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Liu, Qingshan (Computer scientist), editor.
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Wang, Hanzi, editor
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Ma, Zhanyu, editor
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Zheng, Weishi, editor
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Zha, Hongbin, editor.
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Chen, Xilin, editor.
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Wang, Liang, editor
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Ji, Rongrong, 1983- editor.
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| ISBN |
9789819984350 |
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9819984351 |
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