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Libro
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Pattern Recognition and Computer Vision
liu qingshan (curatore); wang hanzi (curatore); ma zhanyu (curatore); zheng weishi (curatore); zha hongbin (curatore); chen xilin (curatore); wang liang (curatore); ji rongrong (curatore)
80,98 €
76,93 €
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TRAMA
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.SOMMARIO
OKGR: Occluded Keypoint Generation and Refinement for 3D Object Detection.- Camouflaged Object Segmentation Based on Fractional Edge Perception.- DecTrans: Person Re-identification with Multifaceted Part Features via Decomposed Transformer.- AHT: A Novel Aggregation Hyper-Transformer for Few-Shot Object Detection.- Feature Refinement from Multiple Perspectives for High Performance Salient Object Detection.- Feature Disentanglement and Adaptive Fusion for Improving Multi-Modal Tracking.- Modality Balancing Mechanism for RGB-Infrared Object Detection in Aerial Image.- Pacific Oyster Gonad Identification and Grayscale Calculation Based on Unapparent Object Detection.- Multi-task Self-supervised Few-Shot Detection.- CSTrack: A Comprehensive and Concise Vision Transformer Tracker.- Feature Implicit Enhancement via Super-Resolution for Small Object Detection.- Improved detection method for SODL-YOLOv7 intensive juvenile abalone.- MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation.- Context-FPN and Memory Contrastive Learning for Partially Supervised Instance Segmentation.- A Dynamic Tracking Framework Based on Scene Perception.- HPAN: A Hybrid Pose Attention Network for Person Re-identification.- SpectralTracker: Jointly High and Low-Frequency Modeling for Tracking.- DiffusionTracker: Targets Denoising based on Diffusion Model for Visual Tracking.- Instance-proxy Loss for Semi-supervised Learning with Coarse Labels.- FAFVTC: A Real-time Network for Vehicle Tracking and Counting.- Ped-Mix: Mix Pedestrians for Occluded Person Re-Identification.- Object-Aware Transfer-based Black-box Adversarial Attack on Object Detector.- HTNet: A Hybrid Model Boosted by Triple Self-Attention for Crowd Counting.- Reliable Boundary Samples-based Proxy Pairs for Unsupervised Person Re- dentification.- High-Resolution Feature Representation Driven Infrared Small-Dim Object Detection.- Few-Shot Object Detection Algorithm Based on Adaptive Relation Distillation.- A real-time safety detector based on re-parameterization multiscale feature fusion for forklift driving.- RTMDet-R2:An Improved Real-Time Rotated Object Detector.- Boosting Object Detection in Foggy Scenes via Dark Channel Map and Union Training Strategy.- Object Centric Body Part Attention Network for Human-Object Interaction Detection.- Salient Feature Enhanced Multi-Object Tracking with Soft-Sparse Attention in Transformer.- A BiGRU based Adaptive Gain Estimation for radar Multi-target Tracking.- Prompt based Lifelong Person Re-identification.- Hierarchical Focused Feature Pyramid Network for Small Object Detection JLInst: Boundary-Mask Joint Learning for Instance Segmentation.- Boosting One-stage Multi Object Tracking with Attention Learning.- TPNet: Enhancing Weakly Supervised Polyp Frame Detection with Temporal Encoder and Prototype-based Memory Bank.- Learning Frequency-based Disentanglement and Filtering for Generalizable Person Re-identification.- Stereo3DMOT: Stereo Vision Based 3D Multi-Object Tracking with Multimodal ReID.- Emphasizing Boundary-Positioning and Leveraging Multi-Scale Feature Fusion for Camouflaged Object DetectionALTRE INFORMAZIONI
- Condizione: Nuovo
- ISBN: 9789819985548
- Collana: Lecture Notes in Computer Science
- Dimensioni: 235 x 155 mm Ø 819 gr
- Formato: Brossura
- Illustration Notes: XIV, 523 p. 203 illus., 194 illus. in color.
- Pagine Arabe: 523
- Pagine Romane: xiv