Edge-Assisted On-Device Model Update for Video Analytics in Adverse Environments-Reference-Cited by-同舟云学术

Edge-Assisted On-Device Model Update for Video Analytics in Adverse Environments

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Kong Yuxin¹^ORCID,Yang Peng²^ORCID,Cheng Yan²^ORCID

Affiliation:

1. Huazhong University of Science and Technology, Wuhan, Chile

2. Huazhong University of Science and Technology, Wuhan, China

Funder

Natural Science Foundation of Hubei Province of China

Young Elite Scientists Sponsorship Program by CAST

Natural Science Foundation of China

Fundamental Research Funds for the Central Universities, HUST

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612585

Reference58 articles.

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2. Romil Bhardwaj , Zhengxu Xia , Ganesh Ananthanarayanan , Junchen Jiang , Yuanchao Shu , Nikolaos Karianakis , Kevin Hsieh , Paramvir Bahl , and Ion Stoica . 2022 . Ekya: Continuous learning of video analytics models on edge compute servers . In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22) . 119--135. Romil Bhardwaj, Zhengxu Xia, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Nikolaos Karianakis, Kevin Hsieh, Paramvir Bahl, and Ion Stoica. 2022. Ekya: Continuous learning of video analytics models on edge compute servers. In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22). 119--135.

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4. Deep Learning With Edge Computing: A Review

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