원문정보
한국차세대컴퓨팅학회
한국차세대컴퓨팅학회 학술대회
The 8th International Conference on Next Generation Computing 2022
2022.10
pp.83-85
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
A safe and robust autonomous driving system relies on accurate perception of the environment for application-oriented scenarios. This paper proposes deployment of the three most crucial tasks (i.e., object detection, drivable area segmentation and lane detection tasks) on embedded system for self-driving operations. To achieve this research objective, multi-tasking network is utilized with a simple encoder-decoder architecture. Comprehensive and extensive comparisons for two models based on different backbone networks are performed. All training experiments are performed on server while Nvidia Jetson Xavier NX is chosen as deployment device.
목차
Abstract
I. INTRODUCTION
II. METHOD
A. Network architecture
B. Implementation details
III. EXPERIMENTS AND RESULTS
A. Model size and running efficiency
B. Qualitative Results
IV. CONCLUSION
REFERENCES
I. INTRODUCTION
II. METHOD
A. Network architecture
B. Implementation details
III. EXPERIMENTS AND RESULTS
A. Model size and running efficiency
B. Qualitative Results
IV. CONCLUSION
REFERENCES
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저자정보
참고문헌
자료제공 : 네이버학술정보