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YOLO 네트워크를 사용한 다중 차선 인식

원문정보

Multi-Lanes Recognition using the YOLO Network

박진현, 박희문

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초록

영어

Future autonomous vehicles need to recognize the ego lanes required for lane change and the side left and right lanes differently. Therefore, multi-lane recognition is needed. In this study, using the YOLO network, mainly used for object recognition, the proposed method recognizes the ego, left and right side lanes as different objects and identifies the correct lanes. As a result of the performance evaluation on the TuSimple test data, the proposed method recognized the ego lanes and the left and right side lanes differently. It showed very stable lane recognition results. And by detecting lanes that do not exist in the ground truth of TuSimple data, the proposed method is very robust in lanes detection. Nevertheless, studies related to learning data reinforcement in which lanes are located in the center or at the left and right edges of the image and accurate network learning for lanes are needed.

목차

ABSTRACT
1. 서론
2. YOLO를 이용한 차선 검출 방법
2.1 차선 검출 방법
2.2 YOLO 네트워크의 학습데이터
3. YOLO에 의한 차선 인식 시스템
4. 모의실험 및 결과
5. 결론
References

저자정보

  • 박진현 Jin-Hyun Park. Member, Professor, Dept. of Mechatronics Eng., Gyeongsang National University
  • 박희문 Hee-Mun Park. Student, Dept. of Mechatronics Eng., Gyeongsang National University

참고문헌

자료제공 : 네이버학술정보

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