Multi-instance mining with dynamic localization for weakly supervised object detection in remote-sensing images

Chen Guo; Zhenyu Ma; Yangyang Zhao; Chuanshuo Cao; Zhiguo Jiang; Haopeng Zhang

doi:10.1080/01431161.2025.2479886

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-instance mining with dynamic localization for weakly supervised object detection in remote-sensing images

Chen Guo Zhenyu Ma Yangyang Zhao Chuanshuo Cao Zhiguo Jiang Haopeng Zhang

Year: 2025 Journal: International Journal of Remote Sensing Vol: 46 (9)Pages: 3487-3512 Publisher: Taylor & Francis

DOI: 10.1080/01431161.2025.2479886

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Remote sensing Artificial intelligence Object (grammar) Object detection Computer vision Pattern recognition (psychology) Data mining Geography

Metrics

Cited By

9.55

FWCI (Field Weighted Citation Impact)

Refs

0.91

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Multi-instance mining with dynamic localization for weakly supervised object detection in remote-sensing images

Metrics

Citation History

Topics

Related Documents

High-Quality Instance Mining and Dynamic Label Assignment for Weakly Supervised Object Detection in Remote Sensing Images

Weakly supervised object detection from remote sensing images via self-attention distillation and instance-aware mining

Progressive Contextual Instance Refinement for Weakly Supervised Object Detection in Remote Sensing Images

High-Quality Instance Mining and Weight Re-Assigning for Weakly Supervised Object Detection in Remote Sensing Images

Object Instance Mining for Weakly Supervised Object Detection