Summary Embedded Deep Learning Object Detection Model Competition

Jiun-In Guo, Chia Chi Tsai, Yong Hsiang Yang, Hung Wei Lin, Bo Xun Wu, Ted T. Kuo, Li Jen Wang

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

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.

原文English
主出版物標題IEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728118178
DOIs
出版狀態Published - 九月 2019
事件21st IEEE International Workshop on Multimedia Signal Processing, MMSP 2019 - Kuala Lumpur, Malaysia
持續時間: 27 九月 201929 九月 2019

出版系列

名字IEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019

Conference

Conference21st IEEE International Workshop on Multimedia Signal Processing, MMSP 2019
國家Malaysia
城市Kuala Lumpur
期間27/09/1929/09/19

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