Improved YOLOv5s Algorithm for Small Target Detection in UAV Aerial Photography
Author:
Affiliation:
1. School of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, China
2. Fu Foundation School of Engineering and Applied Science, Columbia University, New York, NY, USA
Funder
National Key Research and Development Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10398197.pdf?arnumber=10398197
Reference17 articles.
1. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
2. SSD: Single Shot MultiBox Detector
3. You only look once: Unified, real-time object detection;Redmon;arXiv:1506.02640,2015
4. An Improved YOLOv5 Method for Small Object Detection in UAV Capture Scenes
5. Real-Time Vehicle Detection from UAV Aerial Images Based on Improved YOLOv5
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. YOLO-LE: A lightweight and efficient UAV aerial image target detection model;2024-09-12
2. HeMoDU: High-Efficiency Multi-Object Detection Algorithm for Unmanned Aerial Vehicles on Urban Roads;Sensors;2024-06-21
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