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End-to-End Learning-based Self-Driving Control Imitating Human Driving
- Kim, Donghyun;
- Kwon, Jaerock;
- Nam, Haewoon
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4초록
In recent years, End-to-End learning-based self-driving cars have been actively researched. Unlike conventional methods, neural networks are trained to drive like human drivers by mapping directly from sensory data to control commands. In this paper, we propose a neural network architecture for recognizing visual information and controlling the steering and speed of the vehicle like humans.
키워드
End-to-End learning; Autonomous driving
- 제목
- End-to-End Learning-based Self-Driving Control Imitating Human Driving
- 저자
- Kim, Donghyun; Kwon, Jaerock; Nam, Haewoon
- 발행일
- 2021-10
- 유형
- Proceedings Paper
- 저널명
- 12TH INTERNATIONAL CONFERENCE ON ICT CONVERGENCE (ICTC 2021): BEYOND THE PANDEMIC ERA WITH ICT CONVERGENCE INNOVATION
- 권
- 2021-October
- 페이지
- 1763 ~ 1765
- 언어
- ENG
- 출판사
- IEEE
- 발행국가
- 미국
- 분량
- 3 페이지
- ISSN
- P 2162-1233