@inproceedings{0905457058f442c0b2f9dd8a4f71b584,
title = "A Study for Selecting the Best One-Stage Detector for Autonomous Driving",
abstract = "A development of deep learning has accelerated research into autonomous driving. Especially, deep-learning based object detection has been actively studied and has become an essential technology for autonomous driving. In this paper, the representative one-stage detectors are evaluated and compared using the autonomous driving dataset, and the best algorithm is proposed in terms of trade-off between detection accuracy and processing speed. In addition, the effect of input size in utilizing this algorithm for autonomous driving application is analyzed through various experiments, and finally the most suitable input size for autonomous driving is proposed.",
keywords = "Autonomous driving, Object detection, One-stage detector, YOLOv3",
author = "Dayoung Chun and Jiwoong Choi and Hyun Kim and Lee, \{Hyuk Jae\}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 ; Conference date: 23-06-2019 Through 26-06-2019",
year = "2019",
month = jun,
doi = "10.1109/ITC-CSCC.2019.8793291",
language = "English",
series = "34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019",
}