Enhanced YOLOv8 algorithm for large-scale multi-object detection and its application in defect detection in power systems

Yong Su; Zhen Qiu; Xiaoguang Huang; Dawei Lu

doi:10.1117/12.3024240

13 May 2024 Enhanced YOLOv8 algorithm for large-scale multi-object detection and its application in defect detection in power systems

Yong Su, Zhen Qiu, Xiaoguang Huang, Dawei Lu

Author Affiliations +

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 1315988 (2024) https://doi.org/10.1117/12.3024240
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

Defect detection in power systems is crucial for ensuring the safety, stability, and reliable operation of these systems. However, traditional image recognition algorithms face challenges such as low accuracy, slow speed, and poor generalization when dealing with large-scale multi-object detection tasks. This paper proposes an enhanced YOLOv8 algorithm for large-scale multi-object detection and applies it to defect detection in power systems. The proposed method introduces attention mechanisms, multi-scale feature fusion, and adaptive anchor box generation techniques based on the YOLOv8 algorithm, thereby improving the model’s detection accuracy and robustness. Experiments were conducted on a publicly available power system image datasets and compared with algorithms such as YOLOv8, YOLOv5, and Faster R-CNN. The experimental results demonstrate that the proposed method has a significant advantage in large-scale multi-object detection, achieving a mean average precision (mAP) of 90.2.

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

Citation Download Citation

Yong Su, Zhen Qiu, Xiaoguang Huang, and Dawei Lu "Enhanced YOLOv8 algorithm for large-scale multi-object detection and its application in defect detection in power systems", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 1315988 (13 May 2024); https://doi.org/10.1117/12.3024240

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
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Object detection

Detection and tracking algorithms

Defect detection

Feature fusion

Education and training

Head

Image fusion

Show All Keywords

Keywords/Phrases

Search In:

Publication Years