標題: Summary Embedded Deep Learning Object Detection Model Competition
作者: Guo, Jiun-In
Tsai, Chia-Chi
Yang, Yong-Hsiang
Lin, Hung-Wei
Wu, Bo-Xun
Kuo, Ted T.
Wang, Li-Jen
交大名義發表
電子工程學系及電子研究所
National Chiao Tung University
Department of Electronics Engineering and Institute of Electronics
關鍵字: Object detection;Autonomous driving vehicles;Embedded deep learning
公開日期: 1-一月-2019
摘要: The embedded deep learning object detection model competition in IEEE MMSP2019 focuses on the object detection for sensing technology in autonomous driving vehicles, which aims at detecting small objects in worse conditions through embedded systems. We provide a dataset with 89,002 annotated images for training and 1,500 annotated images for validation. We test participants' models through 6,000 testing images, which are separated into 3,000 for qualification and 3,000 for finals. There are 87 teams of participants registered this competition and 14 teams submitted the team composition. At last there are nine teams entering the final competition and five teams submitting their final models that can be realized in NVIDIA Jetson TX-2. At the end, only one team's model passed the target accuracy requirement for grading and became the champion of the contest, which the winner is team R.JD.
URI: http://hdl.handle.net/11536/154002
ISBN: 978-1-7281-1817-8
ISSN: 2163-3517
期刊: 2019 IEEE 21ST INTERNATIONAL WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING (MMSP 2019)
起始頁: 0
結束頁: 0
顯示於類別:會議論文