EA‐YOLO: An Efficient and Accurate UAV Image Object Detection Algorithm

An improved EA‐YOLO object detection algorithm based on YOLOv5 is proposed to address the issues of drastic changes in target scale, low detection accuracy, and high miss rate in unmanned aerial vehicle aerial photography scenarios. Firstly, a DFE module was proposed to improve the effectiveness of...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEJ transactions on electrical and electronic engineering Jg. 20; H. 1; S. 61 - 68
Hauptverfasser:	Dong, Dehao, Li, Jianzhuang, Liu, Haiying, Deng, Lixia, Gu, Jason, Liu, Lida, Li, Shuang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken, USA John Wiley & Sons, Inc 01.01.2025 Wiley Subscription Services, Inc
Schlagworte:	Aerial photography Algorithms deep learning Effectiveness Feature extraction Feature maps Object recognition real‐time detection small object detection Target detection UAV image Unmanned aerial vehicles YOLOv5
ISSN:	1931-4973, 1931-4981
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!