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

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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 1820, 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.
Anchored Supervised Contrastive Learning for Long-Tailed Medical Image
Regression.- Dynamic Feature Fusion Based on Consistency and Complementarity
of Brain Atlases.- FUF-TransUNet: a transformer-based U-Net with fully
utilize of features for liver and liver-tumor segmentation in CT images.-
Dual-View Dual-Boundary Dual U-Nets for Multiscale Segmentation of Oral CBCT
ImagesA Novel Diffusion Model with Wavelet Transform for Optic Disc and Cup
Segmentation in Fundus Images.- STCTb: A Spatio-Temporal Collaborative
Transformer Block for Brain Diseases Classification using fMRI Time Series.A
Generalized Contrast-adjustment Guided Growth Method for Medical Image
Segmentation.- MDNet: Morphology-Driven Weakly Supervised Polyp
DetectionMMR-Sleep: A Multi-Channel and  Multi-Receptive Field Sleep Stage
recognition  Model.- CPNet: Cross Prototype Network for Few-shot Medical
Image Segmentation.- SBC-UNet: A Network Based on Improved Hourglass
Attention Mechanism and U-Net for Medical Image Segmentation.- Bridge the gap
of semantic context: A Boundary-guided Context Fusion UNet for Medical Image
Segmentation.- Bilinear Fine-grained Classification of Ultrasound Images
Integrated with Interpretable Radiomics.- GCNet: Global context-guided
uncertainty boundary for polyp segmentation.- Comprehensive Transformer
Integration Network (CTIN): Advancing Endoscopic Disease Segmentation with
Hybrid Transformer Architecture.- IPM: An Intelligent Component for 3D Brain
Tumor Segmentation Integrating Semantic Extractor and Pixel RefinerEdge-Net:
A Self-supervised Medical Image Segmentation Model Based on Edge Attention.-
Fundus image disease diagnosis and quality assessment based on dual-task
collaborative optimization.- Multi-modality Correlation Learning Network for
Pediatric Ventricular Septal Defects Identification.- MFIS-net: A Deep
Learning Framework for Left Atrial Segmentation.- Semi-Supervised Gland
Segmentation via Label Purification and Reliable Pixel Learning.- DFANet: A
Dual-stream Deep Feature Aware Network for Multi-focus Image
FusionMST-GaitApplication of Multi-Scale Temporal Modeling to Gait
Recognition.- Identity-Preserving Animal Image Generation for Animal
Individual Identification.- FIL-FLD: Few-shot Incremental Learning with EMD
Metric for High Generalization Fingerprint Liveness DetectionText Based
Unsupervised Domain Generalization Person Re-identificationSF-Gait: Two-Stage
Temporal Compression Network for Learning Gait Micro-Motions and Cycle
Patterns.- Coarse-to-Fine Domain Adaptation for Cross-subject EEG Emotion
Recognition with Contrastive Learning.- Face Anti-spoofing based on
Multi-view Anomaly Detection. -Online Signature Verification Based on
Recurrent Attentional Time-Delay Neural Networks.- Multimodal finger
recognition based on feature fusion  attention for fingerprints,
finger-veins, and  f  inger-knuckle-prints. -Hierarchical Discrepancy-aware
Interaction Network for Face Forgery DetectionAU-vMAE: Knowledge-Guide Action
Units Detection via Video Masked AutoencoderTransformer-based Multimodal
Spatial-Temporal Fusion for Gait Recognition.- Multi-level Distributional
Discrepancy Enhancement for Cross Domain Face Forgery Detection.-
Unsupervised person Re-ID based on nonlinear asymmetric metric learning.-
FR-watermarking: A Fusion Framework for Face-Based Digital Watermarking.-
Enhancing Semi-Dense Feature Matching through Probabilistic Modeling of
Cascaded Supervision and Consistency.- Concentrating Estimation Attention:
Human Prior Constrained Methods for Robust Classification.
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