Overview

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 13–15, 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. 

Full Product Details

Author:   Qingshan Liu ,  Hanzi Wang ,  Zhanyu Ma ,  Weishi Zheng
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   1st ed. 2024
Volume:   14432
Weight:   0.801kg
ISBN:  

9789819985425

ISBN 10:   9819985420
Pages:   513
Publication Date:   03 January 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

A Quantum-based Attention Mechanism in Scene Text Detection.- NCMatch: Semi-Supervised Learning with Noisy Labels via Noisy Sample Filter and Contrastive Learning.- Data-free Low-bit Quantization via Dynamic Multi-teacher Knowledge Distillation.- LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation.- DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation.- Space-Transform Margin Loss with Mixup for Long-tailed Visual Recognition.- A Multi-Perspective Squeeze Excitation Classifier Based on Vision Transformer for Few Shot Image Classification.- ITCNN: Incremental Learning Network Based on ITDA and Tree Hierarchical CNN.- Periodic-Aware Network for Fine-grained Action Recognition.- Learning Domain-invariant Representations from Text for Domain Generalization.- TSTD:A Cross-modal Two Stages Network with New Trans-Decoder for Point Cloud Semantic Segmentation.- NeuralMAE: Data-Efficient Neural Architecture Predictor with Masked Autoencoder.- Co-Regularized Facial Age Estimation with Graph-Causal Learning.- Online Distillation and Preferences Fusion for Graph Convolutional Network-based Sequential Recommendation.- Grassmann Graph Embedding for Few-Shot Class Incremental Learning.- Global Variational Convolution Network for Semi-Supervised Node Classification on Large-scale Graphs.- Frequency Domain Distillation for Data-Free Quantization of Vision Transformer.- An ANN-Guided Approach to Task-Free Continual Learning with Spiking Neural Networks.- Multi-Adversarial Adaptive Transformers for Joint Multi-Agent Trajectory Prediction.- Enhancing Open-Set Object Detection via Uncertainty-Boxes Identification.- Interventional Supervised Learning for Person Re-Identification.- DP-INNet: Dual-Path Implicit Neural Network for Spatial and Spectral Features Fusion in Pan-sharpening.- Stable Visual Pattern Mining via Pattern Probability Distribution.- Dynamic Visual Prompt Tuning for Parameter Efficient Transfer Learning.- C-volution: A Hybrid operator for Visual Recognition.- Motor Imagery EEG Recognition Based on an Improved Convolutional Neural Network with Parallel Gate Recurrent Unit.- A Stable Vision Transformer for Out-of-Distribution Generalization.- Few-Shot Classification with Semantic Augmented Activators.- MixPose: 3D Human Pose Estimation with Mixed Encoder.- Image Manipulation Detection Based on Ringed Residual Edge Artifact Enhancement and Multiple Attention Mechanisms.- Improving Masked Autoencoders by Learning Where to Mask.- An Audio Correlation-Based Graph Neural Network for Depression Recognition.- Dynamic Gesture Recognition based on 3D Central Difference Separable Residual LSTM Coordinate Attention Networks.- QESAR: Query Effective Decision-based Attack on Skeletal Action Recognition.- A Closer Look at Few-shot Object Detection.- Learning-without-Forgetting via Memory Index in Incremental Object Detection.- SAMDConv: Spatially Adaptive Multi-scale Dilated Convolution.- SADD:Generative Adversarial Networks via Self-Attention and Dual Discriminator in Unsupervised Domain Adaptation.- ELFLN: An Efficient Lightweight Facial Landmark Network Based on Hybrid Knowledge Distillation.- Enhancing Continual Noisy Label Learning with Uncertainty-based Sample Selection and Feature Enhancement

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