Pattern Recognition and Computer Vision -

Pattern Recognition and Computer Vision

5th Chinese Conference, PRCV 2022, Shenzhen, China, November 4–7, 2022, 2022, Proceedings, Part IV
Buch | Softcover
XVII, 737 Seiten
2022 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-031-18915-9 (ISBN)
53,49 inkl. MwSt
The 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022.
The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.

Image Processing and Low-level Vision.- Video Deraining via Temporal Discrepancy Learning.- Multi-priors Guided Dehazing Network Based on Knowledge Distillation.- DLMP-Net: a dynamic yet lightweight multi-pyramid network for crowd density estimation.- CHENet: Image to Image Chinese Handwriting Eraser.- Identidication method for rice pests with small sample size problem combining deep learning and metric learning.- Boundary-Aware Polyp Segmentation Network.- SUDANet:A Siamese UNet with Dense Attention Mechanism for Remote Sensing Image Change Detection.- A Local-Global Self-attention Interaction Network for RGB-D Cross-modal Person Re-identification.- A RAW Burst Super-Resolution Method with Enhanced Denoising.- Unpaired and Self-supervised Optical Coherence Tomography Angiography Super-resolution.- Multi-Feature Fusion Network for Single Image Dehazing.- LAGAN: Landmark Aided Text to Face Sketch Generation.- DMF-CL: Dense Multi-scale Feature Contrastive Learning for Semantic segmentation of Remote-sensing images.- Image derain method for generative adversarial network based on wavelet high frequency feature fusion.- GPU-Accelerated Infrared Patch-Image Model for Small Target Detection.- Hyperspectral and Multispectral Image Fusion Based on Unsupervised Feature Mixing and Reconstruction Network.- Information Adversarial Disentanglement for Face Swapping.- A Dense Prediction ViT Network for Single Image Bokeh Rendering.- Multi-scale Coarse-to-fine Network for Demoiring.- Learning Contextual Embedding Deep Networks for Accurate and Efficient Image Deraining.- A Stage-Mutual-Ane Network for Single Remote Sensing Image Super-Resolution.- Style-based Attentive Network for Real-World Face Hallucination.- Cascade Scale-aware Distillation Network for Lightweight RemoteSensing Image Super-Resolution.- Few-Shot Segmentation via Rich Prototype Generation and RecurrentPrediction Enhancement.- Object Detection, Segmentation and Tracking.- TAFDet: A Task Awareness Focal Detector for Ship Detection in SAR Images.- MSDNet:Multi-scale Dense Networks for Salient Object Detection.- WaveSNet: Wavelet Integrated Deep Networks for Image Segmentation.- Infrared Object Detection Algorithm Based on Spatial Feature Enhancement.- Object Detection Based on Embedding Internal and External Knowledge.- ComLoss: A Novel Loss towards More Compact Predictions for Pedestrian Detection.- Remote sensing image detection based on attention mechanism and YOLOv5.- Detection of Pin Defects in Transmission Lines Based on Dynamic Receptive Field.- Identification of bird s nest hazard level of transmission line based on improved yolov5 and location constraints.- Image Magnification Network for Vessel Segmentation in OCTA Images.- CFA-Net: Cross-level Feature Fusion and Aggregation Network for Salient Object Detection.- Disentangled Feature Learning for Semi-supervised Person Re-identification.- Detection Beyond What and Where: A Benchmark for Detecting Occlusion State.- Weakly Supervised Object Localization with Noisy-Label Learning.- Enhanced Spatial Awareness For Deep Interactive Image Segmentation.- Anchor-Free Location Refinement Network for Small License Plate Detection.- Multi-View LiDAR Guided Monocular 3D Object Detection.- Dual Attention-guided Network for Anchor-free Apple Instance Segmentation in Complex Environments.- Attention-Aware Feature Distillation for Object Detection in Decompressed Images.- Cross-Stage Class-Specific Attention for Image Semantic Segmentation.- Defect Detection for High Voltage Transmission Lines Based on Deep Learning.- ORION: Orientation-Sensitive Object Detection.- An Infrared MovingSmall Object Detection Method Based on Trajectory Growth.- Two-stage Object Tracking Based on Similarity Measurement for FusedFeatures of Positive and Negative Samples.- PolyTracker: Progressive Contour Regression for Multiple ObjectTracking and Segmentation.- Dual-branch Memory Network for Visual Object Tracking.- Instance-wise Contrastive Learning for Multi-Object Tracking.- Information Lossless Multi-Modal Image Generation for RGB-T Tracking.- JFT: A Robust Visual Tracker Based on Jitter Factor and Global Registration.- Caged Monkey Dataset: A New Benchmark for Caged Monkey Pose Estimation.- WTB-LLL: A Watercraft Tracking Benchmark Derived by Low-light-level Camera.- Dualray: Dual-view X-ray Security Inspection Benchmark and FusionDetection Framework.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Zusatzinfo XVII, 737 p. 322 illus., 319 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 1139 g
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Applications • Artificial Intelligence • Computer Hardware • Computer Networks • Computer Science • computer vision • conference proceedings • Image Analysis • image enhancement • Image Processing • Image Quality • image reconstruction • Image Segmentation • Imaging Systems • Informatics • Information Retrieval • machine learning • Neural networks • Object detection • Object recognition • pattern recognition • Research • Signal Processing
ISBN-10 3-031-18915-9 / 3031189159
ISBN-13 978-3-031-18915-9 / 9783031189159
Zustand Neuware
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