Boosting Mobile CNN Inference through Semantic Memory-Reference-Cited by-同舟云学术

Boosting Mobile CNN Inference through Semantic Memory

Published:2021-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Multimedia
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Author:

Li Yun¹,Zhang Chen²,Han Shihao³,Zhang Li Lyna⁴,Yin Baoqun¹,Liu Yunxin⁵,Xu Mengwei⁶

Affiliation:

1. University of Science and Technology of China, Hefei, UNK, China

2. Damo Academy, Alibaba Group, Shanghai, UNK, China

3. Rose-Hulman Institute of Technology, Terre Haute, UNK, USA

4. Microsoft Research, Beijing, UNK, China

5. Institute for AI Industry Research (AIR), Tsinghua University, Beijing, UNK, China

6. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, UNK, China

Funder

the Fundamental Research Funds for the Central Universities and National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3474085.3475399

Reference58 articles.

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3. 2021. General Data Protection Regulation (GDPR). https://gdpr-info.eu/. 2021. General Data Protection Regulation (GDPR). https://gdpr-info.eu/.

4. John A Bargh and Tanya L Chartrand. 2000. Studying the mind in the middle: a practical guide to priming and automaticity research. Handbook of research methods in social psychology. Handbook of research methods in social and personality psychology (2000) 253--285. John A Bargh and Tanya L Chartrand. 2000. Studying the mind in the middle: a practical guide to priming and automaticity research. Handbook of research methods in social psychology. Handbook of research methods in social and personality psychology (2000) 253--285.

5. EVA²: Exploiting Temporal Redundancy in Live Computer Vision

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