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다중 차선 인식을 위한 YOLO의 적용Application of YOLO for Multi-Lanes Recognition

Other Titles
Application of YOLO for Multi-Lanes Recognition
Authors
박성찬박희문박진현
Issue Date
2021
Publisher
한국기계기술학회
Keywords
Autonomous vehichle; Lane recognition; YOLO; Deep learning; Multi-Lanes; 자율주행 차량; 차선 인식; 욜로; 딥러닝; 다중 차선
Citation
한국기계기술학회지, v.23, no.6, pp 1137 - 1145
Pages
9
Indexed
KCI
Journal Title
한국기계기술학회지
Volume
23
Number
6
Start Page
1137
End Page
1145
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/4727
DOI
10.17958/ksmt.23.6.202112.1137
ISSN
1229-604X
2508-3805
Abstract
We need data such as the number of lanes for lane change on the road as well as environmental and object recognition of the road for the autonomous vehicle of the future. This study proposed an algorithm that recognizes the left and right lanes and the center lane while driving differently from the black box image taken from a car. In general, deep learning does not recognize lanes individually but recognizes all lanes as only one lane. Therefore, using YOLO's object recognition function, the left and right lanes and the center lane were detected as different lanes, and a heuristic method was applied to recognize multi-lanes as more correct lanes. As a result of the performance evaluation, we confirmed that the proposed method detects the lane more accurately than Fast R-CNN and only YOLOv2.
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융합기술공과대학 > Division of Mechatronics Engineering > Journal Articles

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