Lightweight target detection model for substation instrumentation and its hardware acceleration for front-end applications

Junjie Chen; Xinhao Hong; Minggui Zhang; Hao Jiang

doi:10.1117/12.3033711

13 June 2024 Lightweight target detection model for substation instrumentation and its hardware acceleration for front-end applications

Junjie Chen, Xinhao Hong, Minggui Zhang, Hao Jiang

Author Affiliations +

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 1318064 (2024) https://doi.org/10.1117/12.3033711
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

With the development of robot technology, intelligent robot has been widely used in substation inspection. However, the current target detection algorithm faces the problem of too many parameters to realize real-time detection on embedded platform. To address this issue, an improved YOLOv5 algorithm based on AI front-end is proposed for substation instrument detection. The algorithm is based on YOLOv5 network and introduces the SE fusion attention mechanism module, which adaptively learns the relationship between feature channels to improve the model's ability to extract important features of objects. At the same time, TensorRT technology is used for reconstruction and optimization to reduce the computation and improve the detection speed. Experimental results show that, compared with YOLOv5, the algorithm at mAP@.5 and mAP@.5:.95 increases 1.5% and 2.3% respectively, and the detection frame number per second increases 150% to reach 25FPS, which provides the possibility for real-time instrument detection in substation scenarios.

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

Citation Download Citation

Junjie Chen, Xinhao Hong, Minggui Zhang, and Hao Jiang "Lightweight target detection model for substation instrumentation and its hardware acceleration for front-end applications", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 1318064 (13 June 2024); https://doi.org/10.1117/12.3033711

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
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Detection and tracking algorithms

Object detection

Evolutionary algorithms

Feature extraction

Instrument modeling

Mathematical optimization

Target detection

Show All Keywords

Keywords/Phrases

Search In:

Publication Years