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다중 차선 인식을 위한 YOLO의 적용

원문정보

Application of YOLO for Multi-Lanes Recognition

박성찬, 박희문, 박진현

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초록

한국어

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.

목차

ABSTRACT
1. 서론
2. YOLO를 이용한 차선 검출 방법
2.1 YOLO
2.2 차선 검출을 위한 YOLO 네트워크 구성
3. 차선 검출을 위한 제안된 방법
3.1 YOLO에 의한 차선 감지 및 차선 인식
3.2 휴리스틱한 방법의 차선 인식
4. 실험 및 결과
4. 결론
References

저자정보

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

참고문헌

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