Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, October 29 – November 1, 2021, Proceedings, Part IV: Lecture Notes in Computer Science, cartea 13022
Editat de Huimin Ma, Liang Wang, Changshui Zhang, Fei Wu, Tieniu Tan, Yaonan Wang, Jianhuang Lai, Yao Zhaoen Limba Engleză Paperback – 8 oct 2021
The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and New Advances in Visual Perception and Understanding.
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| Paperback (4) | 580.25 lei 6-8 săpt. | |
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| Springer International Publishing – 8 oct 2021 | 637.51 lei 6-8 săpt. | |
| Springer International Publishing – 8 oct 2021 | 748.94 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783030880125
ISBN-10: 3030880125
Pagini: 577
Ilustrații: XIX, 577 p. 219 illus., 202 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.83 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics
Locul publicării:Cham, Switzerland
ISBN-10: 3030880125
Pagini: 577
Ilustrații: XIX, 577 p. 219 illus., 202 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.83 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics
Locul publicării:Cham, Switzerland
Cuprins
Machine Learning, Neural Network and Deep Learning.- Edge-Wise One-Level Global Pruning on NAS generated networks.- Convolution Tells Where to Look.- Robust Single-step Adversarial Training with Regularizer.- Texture-guided U-Net for OCT-to-OCTA Generation.- Learning Key Actors and Their Interactions for Group Activity Recognition.- Attributed Non-negative Matrix Multi-Factorization for Data Representation.- Improved Categorical Cross-Entropy Loss for Training Deep Neural Networks with Noisy Labels.- A Residual Correction Approach for Semi-supervised Semantic Segmentation.- Hypergraph Convolutional Network with Hybrid Higher-order Neighbors.- Text-Aware Single Image Specular Highlight Removal.- Minimizing Wasserstein-1 Distance by Quantile Regression for GANs Model.- A Competition of Shape and Texture Bias by Multi-View Image Representation.- Learning Indistinguishable and Transferable Adversarial Examples.- Efficient Object Detection and Classification of Ground Objects fromThermal Infrared Remote Sensing Image Based on Deep Learning.- MEMA-NAS: Memory-Efficient Multi-Agent Neural Architecture Search.- Adversarial Decoupling for Weakly Supervised Semantic Segmentation.- Towards End-to-End Embroidery Style Generation: A Paired Dataset and Benchmark.- Efficient and real-time particle detection via encoder-decoder network.- Flexible Projection Search using Optimal Re-weighted Adjacency for Unsupervised Manifold Learning .- Fabric Defect Detection via Multi-scale Feature Fusion-based Saliency.- Improving Adversarial Robustness of Detectors via Objectness Regularization.- IPE Transformer for Depth Completion with Input-Aware Positional Embeddings.- Enhanced Multi-view Matrix Factorization with Shared Representation.- Multi-level Residual Attention Network for Speckle Suppression.- Suppressing Style-Sensitive Features via Randomly Erasing for Domain Generalizable Semantic Segmentation.- MAGAN: Multi-Attention Generative Adversarial Networks for Text-to-Image Generation.- Dual Attention Based Network with Hierarchical ConvLSTM for Video Object Segmentation.- Distance-based Class Activation Map for Metric Learning.- Reading Pointer Meter through One Stage End-to-End Deep Regression.- Deep Architecture Compression with Automatic Clustering of Similar Neurons.- Attention Guided Spatio-temporal Artifacts Extraction for Deepfake Detection.- Learn the Approximation Distribution of Sparse Coding with Mixture Sparsity Network.- Anti-occluded person re-identification via pose restoration and dual channel feature distance measurement.- Dynamic Runtime Feature Map Pruning.- Special Session: New Advances in Visual Perception and Understanding.- Multi-Branch Graph Network for Learning Human-Object Interaction.- FDEA: Face Dataset with Ethnicity Attribute.- TMD-FS: Improving Few-Shot Object Detection with Transformer Multi-modal Directing.- Feature Matching Network for Weakly-Supervised Temporal Action Localization.- LiDAR-based symmetrical guidance for 3D Object Detection.- Few-shot Segmentation via Complementary Prototype Learning and Cascaded Refinement.- Couple Double-Stage FPNs with Single Pipe-line for solar speckle images deblurring.- Multi-scale Image Partitioning and Saliency Detection for Single Image Blind Deblurring.- CETransformer: Casual Effect Estimation via Transformer Based Representation Learning.- An Efficient Polyp Detection Framework with Suspicious Targets Assisted Training.- Invertible Image Compressive Sensing.- Gradient-free Neural Network Training Based on Deep Dictionary Learning with the Log Regularizer.