DNN-SAM: Split-and-Merge DNN Execution for Real-Time Object Detection-Reference-Cited by-同舟云学术

DNN-SAM: Split-and-Merge DNN Execution for Real-Time Object Detection

Published:2022-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS)
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Author:

Kang Woosung¹,Chung Siwoo¹,Kim Jeremy Yuhyun²,Lee Youngmoon²,Lee Kilho³,Lee Jinkyu⁴,Shin Kang G.⁵,Chwa Hoon Sung¹

Affiliation:

1. DGIST,Dept. of Electrical Engineering and Computer Science,Republic of Korea

2. Hanyang University,Dept. of Robotics,Republic of Korea

3. Soongsil University,School of AI Convergence,Republic of Korea

4. Sungkyunkwan University (SKKU),Dept. of Computer Science and Engineering,Republic of Korea

5. The University of Michigan - Ann Arbor,Dept. of Electrical Engineering and Computer Science,U.S.A

Funder

National Research Foundation of Korea

Publisher

IEEE

Link

Reference39 articles.

1. F1/10: An open-source autonomous cyber-physical platform;o’kelly;arXiv preprint arXiv 1901 00828,2019

4. End-to-end object detection with fully convolutional network;wang;2012 arXiv preprint arXiv,2020

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