Pattern Recognition and Computer Vision
Springer International Publishing (Verlag)
978-3-031-18915-9 (ISBN)
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 | 14.10.2022 |
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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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