Application of Improved Yolo algorithm in the Design of FSAC Racing Real-time Target Detection System
Author: 
Jie SunAuthors Info & Claims
Jie SunAuthors Info & ClaimsPages 26 - 29
Abstract
In order to further improve the accuracy of FSAC racing target detection, this paper explores the modified method of Yolo algorithm, puts it into the design of target detection system, and puts forward the application scheme of system design. The scheme uses k-means algorithm to design clustering processing scheme. By reducing the detection target specification, the control algorithm is developed in ROS system to realize high-precision target detection. The test results show that the target detection accuracy of the system is significantly improved compared with the original algorithm, and the processing efficiency is accelerated.
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Published In
November 2021
112 pages
ISBN:9781450385183
DOI:10.1145/3502827
Copyright © 2021 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 January 2022
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ICAIP 2021
ICAIP 2021: 2021 5th International Conference on Advances in Image Processing
November 12 - 14, 2021
Chengdu, China
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