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E-raamat: Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part II

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Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part IISuurem pilt
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This 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024.
The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.

Auto-USOD: Searching Topology for Underwater Salient Object Detection.-
MBA-NER: Multi-Granularity Entity Boundary-Aware Contrastive Enhanced for
Two-stage Few-Shot Named Entity Recognition.- Meta-Learning Based Knowledge
Distillation for Domain Adaptive Nighttime Segmentation.- Enhancing Zero-Shot
Anomaly Detection: CLIP-SAM Collaboration with Cascaded Prompts.- Towards
Adversarial-Robust Class-Incremental Learning via Progressively Volume-up
Perturbation Generation.- Neighborhood Difference-Enhanced Graph Neural
Network based on Hypergraph for Social Bot Detection.- SRMAE: Masked Image
Modeling for Scale-Invariant Deep Representations.- An Entropy-based
Pseudo-Label Mixup Method for Source-Free Domain Adaptation.- DAMS: Document
Image Steganography with Dual Attention Multi-Scale Encoder-Decoder
Architecture.- Dual-Task Cascaded for Proactive Deepfake Detection Using
QPCET watermarking.- XrGroup: Graph Convolutional Networks for Group-Aware
Pedestrian Trajectory Prediction with Speed information.- Generative
Steganography Based on Dual-Branch Flow.- Invisible Backdoor Attack Through
Singular Value Decomposition.- Self-supervised transformer-based pre-training
method with General Plant Infection dataset.- Spatio-Temporal Perceiving
Network Based Vision Transformer for 6-Hour Precipitation Prediction Using
Multi-Meteorological Factors.- Learning Local Spatial and Global Context
Activation for Visual Recognition.- A Novel Method for Autism Identification
based on Multi-Atlas Features  Fusion and Graph Neural Network.- CRFNet: A
medical image segmentation method using the cross attention mechanism and
refined feature fusion strategy.- SCC-CAM: Weakly Supervised Segmentation on
Brain Tumor MRI with Similarity Constraint and Causality.- Global Structural
Consistency Set Transformer.- IMO-Net: Integrated Memory Optimization Network
for Video Instance Lane Detection.- Lightweight Facial Expression Recognition
Based on Hybrid Multiscale and Multi-Head Collaborative Attention.- Single
model learns multiple styles of Chinese calligraphy via Style Collection
Mechanism.- FusionNet for Interactive Image Segmentation.- Dynamic
Spatial-Temporal Perception Graph Convolutional Networks for Traffic Flow
Forecasting.- Foreign object classification for coal conveyor belts based on
deep learning.- Reducing Memory Footprint in Deep Network Training by
Gradient Space Reutilization.- Interpretable Unsupervised Homography
Estimation.- DRC-NET: Density Reweighted Convolution Network for Edge Curve
Extraction.- Unsupervised Underwater Image Enhancement Combining Imaging
Restoration and Prompt Learning.- Generatice Adversarial Imitation Learning
Algorithm based on Improved Curiosity Module.- Zero-shot Blind Face
Restoration via Conditional Diffusion Sampling.- Task-aware Few-shot Image
Generation via Dynamic Local Distribution Estimation and Sampling.-
Adversarial Training and Contrastive Learning with Bidirectional Transformers
for Sequence Recommendation.- Empathizing Before Generation: A Double-layered
Framework for Emotional Support LLM.
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