Adaptive Feature Fusion With Attention-Guided Small Target Detection in Remote Sensing Images
Author:
Affiliation:
1. Research Center for Space Optical Engineering, Harbin Institute of Technology, Harbin, China
2. Key Laboratory of Space Photoelectric Detection and Perception, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10285489.pdf?arnumber=10285489
Reference53 articles.
1. SA-YOLO: The Saliency Adjusted Deep Network for Optical Satellite Image Ship Detection
2. Study on a New Power Frequency Capacitive Voltage Transducer for Gas Insulated Substations Based on Capacitive Voltage Division
3. Multi-scale traffic vehicle detection based on faster R–CNN with NAS optimization and feature enrichment
4. Improved Faster R-CNN With Multiscale Feature Fusion and Homography Augmentation for Vehicle Detection in Remote Sensing Images
5. TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios
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1. Small Object Detection in Medium–Low-Resolution Remote Sensing Images Based on Degradation Reconstruction;Remote Sensing;2024-07-19
2. Hybrid receptive field network for small object detection on drone view;Chinese Journal of Aeronautics;2024-07
3. A Method for Detecting Aircraft Small Targets in Remote Sensing Images by Using CNNs Fused With Handcrafted Features;IEEE Geoscience and Remote Sensing Letters;2024
4. Self-Supervised Denoising via Blind Feature Extraction and Diffusion-Based Texture Generation;IEEE Transactions on Geoscience and Remote Sensing;2024
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