Improved YOLOv5s Algorithm for Small Target Detection in UAV Aerial Photography
UAV aerial photos tend to have complicated backgrounds and dense targets that vary in size. Applying existing object detection algorithms to such images is often inaccurate and prone to misdetection and omission. To better improve the detection performance of UAV aerial photography, we proposed an i...
Saved in:
Main Authors: | Shixin Li, Chen Liu, Kaiwen Tang, Fanrun Meng, Zhiren Zhu, Liming Zhou, Fankai Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10398197/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
TomatoGuard-YOLO: a novel efficient tomato disease detection method
by: Xuewei Wang, et al.
Published: (2025-01-01) -
A Lightweight Anti-Unmanned Aerial Vehicle Detection Method Based on Improved YOLOv11
by: Yunlong Gao, et al.
Published: (2024-12-01) -
YOLO-UP: A High-Throughput Pest Detection Model for Dense Cotton Crops Utilizing UAV-Captured Visible Light Imagery
by: Chenglei Sun, et al.
Published: (2025-01-01) -
Small target detection in UAV view based on improved YOLOv8 algorithm
by: Xiaoli Zhang, et al.
Published: (2025-01-01) -
Recognition of UAVs in Infrared Images Based on YOLOv8
by: Gang Zhou, et al.
Published: (2025-01-01)