Pattern Recognition and Computer Vision

4th Chinese Conference, PRCV 2021, Beijing, China, October 29 ¿ November 1, 2021, Proceedings, Part III
Herausgegeben:Ma, Huimin; Wang, Liang; Zhang, Changshui; Wu, Fei; Tan, Tieniu; Wang, Yaonan; Lai, Jianhuang; Zhao, Yao

• Broschiertes Buch

Produktbeschreibung

The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 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.

Produktdetails

• Lecture Notes in Computer Science 13021
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-88009-5
• 1st ed. 2021
• Seitenzahl: 656
• Erscheinungstermin: 8. Oktober 2021
• Englisch
• Abmessung: 235mm x 155mm x 36mm
• Gewicht: 978g
• ISBN-13: 9783030880095
• ISBN-10: 3030880095
• Artikelnr.: 62470387

Inhaltsangabe

Low-level Vision and Image Processing.- SaliencyBERT: Recurrent Attention Network for Target-oriented Multimodal Sentiment Classification.- Latency-Constrained Spatial-Temporal Aggregated Architecture Search for Video Deraining.- Semantic-Driven Context Aggregation Network for Underwater Image Enhancement.- A Multi-resolution Medical Image Fusion Network with Iterative Back-Projection.- Multi-Level Discriminator and Wavelet Loss for Image Inpainting with Large Missing Area.- 3D^2Unet: 3D Deformable Unet for Low-Light Video Enhancement.- Single Image Specular Highlight Removal on Natural Scenes.- Document image binarization using visibility detection and point cloud segmentation.- LF-MAGNet: Learning Mutual Attention Guidance of Sub-Aperture Images for Light Field Image Super-Resolution.- Infrared Small Target Detection Based on Weighted Variation Coefficient Local Contrast Measure.- Scale-aware Distillation Network for Lightweight Image Super-Resolution.- Deep Multi-Illumination Fusion for Low-Light Image Enhancement.- Relational Attention with Textual Enhanced Transformer For Image Captioning.- Non-local Network Routing for Perceptual Image Super-Resolution.- Multi-Focus Image Fusion with Cooperative Image Multiscale Decomposition.- An Enhanced Multi-Frequency Learned Image Compression Method.- Noise Map Guided Inpainting Network for Low-Light Image Enhancement.- FIE-GAN: Illumination Enhancement Network for Face Recognition.- Illumination-Aware Image Quality Assessment for Enhanced Low-light Image.- Smooth Coupled Tucker Decomposition for Hyperspectral Image Super-resolution.- Self-Supervised Video Super-Resolution by Spatial Constraint and Temporal Fusion.- ODE-Inspired Image Denoiser: An End-to-End Dynamical Denoising Network.- Image Outpainting with Depth Assistance.- Light-weight Multi-channel Aggregation Network for Image Super-resolution.- Slow Video Detection Based on Spatial-temporal Feature Representation.- Biomedical Image Processing and Analysis.- The NL-SC Net for Skin Lesion Segmentation.- Two-Stage COVID-19 Lung Segmentation from CT Images by Integrating Rib Outlining and Contour Refinement.- Deep Semantic Edge for Cell Counting and Localization in Time-Lapse Microscopy Images.- A Guided Attention 4D Convolutional Neural Network for Modeling Spatio-Temporal Patterns of Functional Brain Networks.- Tiny-FASNet: A Tiny Face Anti-spoofing Method Based on Tiny Module.- Attention-based Node-Edge Graph Convolutional Networks for Identification of Autism Spectrum Disorder Using Multi-Modal MRI Data.- Segmentation of Intracellular Structures in Fluorescence Microscopy Images by Fusing Low-Level Feature.- Interactive Attention Sampling Network for Clinical Skin Disease Image Classification.- Cross-Model Attention Method for Medical Image Enhancement.- Multi-modal Face Anti-Spoofing based on a Single Image.- Non-Significant information Enhancement based Attention Network for Face Anti-Spoofing.- Early Diagnosis of Alzheimer's Disease Using 3D Residual Attention Network Based on Hippocampal Multi-indices Feature Fusion.- HPCReg-Net: Unsupervised U-Net Integrating Dilated Convolution and Residual Attention for Hippocampus Registration.- Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis.- Multimodal Representations Learning and Adversarial Hypergraph Fusion for Early Alzheimer's Disease Prediction.- Model-based gait recognition using graph network with pose sequences.- Multi-directional Attention Network for Segmentation of Pediatric Echocardiographic.- Deep-based Super-angular Resolution for Diffusion Imaging.- A Multiple Scale Encoders Network for Stroke Lesion Segmentation.- Nodule Synthesis and Selection for Augmenting Chest X-ray Nodule Detection.- Dual-Task Mutual Learning for Semi-Supervised Medical Image Segmentation.- DPACN:Dual Prior-guided Astrous Convolutional Network for Adhesive Pulmonary Nodules Segmentation on CT Sequence.- Face Anti-Spoofing Based on Cooperative Pose Analysis.- A Dark and Bright Channel Prior Guided Deep Network for Retinal Image Quality Assessment.- Continual Representation Learning via Auto-Weighted Latent Embeddings on Person ReID.- Intracranial Hematoma Classification Based on the Pyramid Hierarchical Bilinear Pooling.- Multi-Branch Multi-Task 3D-CNN for Alzheimer's Disease Detection.