MSFE-YOLO: An Improved YOLOv8 Network for Object Detection on Drone View-Reference-Cited by-同舟云学术

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MSFE-YOLO: An Improved YOLOv8 Network for Object Detection on Drone View

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Qi Shuaihui¹,Song Xiaofeng²^ORCID,Shang Tongfei³,Hu Xiaochang⁴,Han Kun²

Affiliation:

1. Educational Administration Department, National University of Defense Technology, Changsha, China

2. Test Center, National University of Defense Technology, Xi’an, China

3. College of Information and Communication, National University of Defense Technology, Wuhan, China

4. Beijing Institute of Basic Medical Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Natural Science Basic Research Plan in Shanxi Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/8859/10365397/10606537.pdf?arnumber=10606537

Reference22 articles.

1. Detection and Tracking Meet Drones Challenge

2. A Global-Local Self-Adaptive Network for Drone-View Object Detection

3. Pareto Refocusing for Drone-View Object Detection

4. CFANet: Efficient Detection of UAV Image Based on Cross-Layer Feature Aggregation

5. Real-Time Object Detection Network in UAV-Vision Based on CNN and Transformer

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