| Record Type: |
Electronic resources
: Monograph/item
|
| Title/Author: |
Pattern recognition and computer vision/ edited by Zhouchen Lin ... [et al.]. |
| Reminder of title: |
7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024 : proceedings. |
| remainder title: |
PRCV 2024 |
| other author: |
Lin, Zhouchen. |
| corporate name: |
PRCV (Conference) |
| Published: |
Singapore :Springer Nature Singapore : : 2025., |
| Description: |
xiv, 577 p. :ill. (chiefly color), digital ;24 cm. |
| [NT 15003449]: |
Scale-Adaptive Modulation Meet Compact Axial Transformer for Small Object Detection in UAV-Vision -- Lightweight and Multi-Scale Adaptive Network for Infrared Small Target Detection -- Multi-View Cross-Attention Network for Hyperspectral Object Tracking -- CountMamba: Exploring Multi-directional Selective State-Space Models for Plant Counting -- ECLNet: A Compact Encoder-Decoder Network for Efficient Camouflaged Object Detection -- Few-Shot Object Detection via Disentangling Class-Related Factors in Feature Distribution -- Multi-class token-guided end-to-end weakly supervised image semantic segmentation method -- Dynamic Subframe Splitting and Spatio-Temporal Motion Entangled Sparse Attention for RGB-E Tracking -- DIDNet: An End-to-End Directional Insulator Detection Network based on direction field -- L2FIG-Tracker: l2-norm based Fusion with Illumination Guidance for RGB-D Object TrackingCompleting Saliency from Details -- CDAF3D: Cross-Dimensional Attention Fusion for Indoor 3D Object Detection -- RETrack: Multi-Object Tracking by Associating Proposal Regions -- PGNET: A Real-time efficient model for underwater object detectionA Temporal Recognition Framework for Multi-Sheep Behaviour Using ViTSORT and YOLOv8-MS -- Tracking Transforming Objects: A Benchmark -- Modality-Shared Prototypes for Enhanced Unsupervised Visible-Infrared Person Re-identification -- Vehicle Re-identification with a Pose-aware Discriminative Part Learning Model -- Dual-Teacher Network with SSIM based Reverse Distillation for Anomaly DetectionCFMVOR: Federated Multi-view 3D Object Recognition Based on Compressed Learning -- Enhanced Anomaly Detection using Spatial-Alignment and Multi-scale Fusion -- Confidence-Weighted Teacher: Semi-Supervised Object Detection Based on Confidence Correction -- Shape-Aware Soft Label Assignment and Context Enhancement for Oriented Object Detection -- Chareption: Change-Aware Adaption Empowers Large Language Model for Effective Remote Sensing Image Change Captioning -- Spectral-Spatial Multi-view Sparse Self-Representation for Hyperspectral Band Selection -- Adaptive Cross-spatial Sensing Network for Change Detection -- HANet: Hierarchical Attention Network for Remote Sensing Images Semantic Segmentation -- BiReNet: Bilateral Network with Feature Fusion and Edge Detection for Remote Sensing Images Road Extraction -- Latent Feature Representation-Based Low Rank Subspace Clustering for Hyperspectral Band Selection -- DICMNet: Dynamic Irregular Resnet with Multi-direction Channel Remapping for Remote Sensing Road Extraction -- Discriminative Representation-based Classifier for Few-shot Remote Sensing Classification -- Hyperspectral Image Change Detection via Cross-Sample Slot Attention and Dual Gated Feed-Forward Network -- Hyperspectral Image Super-resolution Based on Dual-domain Gated Attention Network -- Spectral Channel-weighting CAT for Hyperspectral image ClassificationBFRNet: Bimodal Fusion and Rectification Network for Remote Sensing Semantic Segmentation -- SFFAFormer: An Semantic Fusion and Feature Accumulation Approach for Change Detection on Remote Sensing ImagesA Novel Multi-scale Feature Fusion based Network for Hyperspectral and Multispectral Image Fusion -- A Sidelobe-Aware Semi-Deformable Convolutional Ship Detection Network for Synthetic Aperture Radar Imagery -- Feature Exchange and Distribution-based Mining Land Detection Method by Multispectral Imagery. |
| Contained By: |
Springer Nature eBook |
| Subject: |
Computer vision - Congresses. - |
| Online resource: |
https://doi.org/10.1007/978-981-97-8493-6 |
| ISBN: |
9789819784936 |