Transmission line route tree target detection technology based on improved YOLOv5s

Xiaoguang Qiao; Bocheng Li; Lanlan Liu; Shasha Peng; Xin Tao

doi:10.1117/12.3037582

27 September 2024 Transmission line route tree target detection technology based on improved YOLOv5s

Xiaoguang Qiao, Bocheng Li, Lanlan Liu, Shasha Peng, Xin Tao

Author Affiliations +

Proceedings Volume 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024); 132751S (2024) https://doi.org/10.1117/12.3037582
Event: 6th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 2024, Wuhan, China

Abstract

Aiming at the problem of low target detection accuracy in unmanned aerial vehicle (UAV) inspection, this paper proposes a target detection algorithm based on improved YOLOv5s for transmission line routes and trees. Firstly, a squeeze-excitation (SE) module is introduced into the backbone network of YOLOv5s, which selectively emphasizes feature information using global information, suppresses non critical features, and recalibrates features. Secondly, the traditional pyramid feature fusion structure of YOLOv5s is replaced with a bifrustum feature fusion (BFF) structure to enhance the extraction ability of validity information and reduce the influence of interference information on recognition accuracy. By constructing an inspection dataset for experimental verification, the results showed that the improved YOLOv5s achieved a MAP of 91.26%, and the detection accuracy of lines and trees reached 94.5% and 89.37%, respectively. The improved model improves detection accuracy while balancing speed, demonstrating the effectiveness of the algorithm.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaoguang Qiao, Bocheng Li, Lanlan Liu, Shasha Peng, and Xin Tao "Transmission line route tree target detection technology based on improved YOLOv5s", Proc. SPIE 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 132751S (27 September 2024); https://doi.org/10.1117/12.3037582

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
5 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Object detection

Feature fusion

Education and training

Inspection

Target detection

Detection and tracking algorithms

Unmanned aerial vehicles

Show All Keywords

Keywords/Phrases

Search In:

Publication Years