Improved YOLOv8 Object Detection Method for Drone Aerial Images
A new improved YOLOv8 drone aerial image object detection method, referred to as the BDI-YOLO model, is proposed to address the problems of small target object size and blurry feature information in drone aerial images, which can lead to missed and false detections. Firstly, the Bidirectional Featur...
Saved in:
| Main Author: | Zhong Shuai, Wang Liping |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Aero Weaponry
2025-06-01
|
| Series: | Hangkong bingqi |
| Subjects: | |
| Online Access: | https://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2024-0163.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DCE-YOLOv8: Lightweight and Accurate Object Detection for Drone Vision
by: Jinsu An, et al.
Published: (2024-01-01) -
Recognition of Maize Tassels Based on Improved YOLOv8 and Unmanned Aerial Vehicles RGB Images
by: Jiahao Wei, et al.
Published: (2024-11-01) -
Eagle-YOLOv8: UAV Object Detection Inspired by the Eagle-Eye Vision System
by: Dianwei Wang, et al.
Published: (2025-01-01) -
Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model
by: Changjiang Liang, et al.
Published: (2025-04-01) -
UAVAI-YOLO: dense small target detection algorithm based on UAV aerial images
by: HE Zhiqian, et al.
Published: (2024-06-01)