CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 13250 > Article
Paper
23 August 2024 A fast tree obstacle small target location algorithm for electric power operation scene based on self-supervised vision transformer
Yang Luo, Siming He, Chen Li, Shaoqing Zuo, Bishun Zhao, Min Xu
Author Affiliations +
Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 132501Q (2024) https://doi.org/10.1117/12.3038670
Event: Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia
Abstract
Conventional fast location algorithm for small target in power operation scene tree obstacle mainly uses ECKF (Embedded Cube Kalman Filter) embedded volume Kalman filter to create a random location function, which is vulnerable to changes in random parameters, resulting in poor location performance. Therefore, a fast location algorithm for small target in power operation scene tree obstacle based on self supervised visual transformer is proposed. That is to say, the self supervised vision transformer is used to design a fast positioning framework for small targets in the power operation scene tree obstacle, thus generating a fast positioning optimization algorithm for small targets in the power operation scene tree obstacle. The experimental results show that the designed fast location algorithm for small target with tree obstacle has high location accuracy, low miss detection rate and false detection rate, which proves that the designed fast location method for small target with tree obstacle in power operation scenarios has good location performance, effectiveness and certain application value, and has made certain contributions to reducing the risk of power operation.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Yang Luo, Siming He, Chen Li, Shaoqing Zuo, Bishun Zhao, and Min Xu "A fast tree obstacle small target location algorithm for electric power operation scene based on self-supervised vision transformer", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 132501Q (23 August 2024); https://doi.org/10.1117/12.3038670
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
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
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Detection and tracking algorithms
Small targets
Transformers
Visualization
Mathematical optimization
Algorithm development
Design
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top