RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network With IP Protection for Internet of Things-Reference-Cited by-同舟云学术

RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network With IP Protection for Internet of Things

Published:2023-04 Issue:4 Volume:42 Page:1185-1198
ISSN:0278-0070
Container-title:IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
language:
Short-container-title:IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

Author:

Qiu Huming¹,Ma Hua²,Zhang Zhi³^ORCID,Gao Yansong¹^ORCID,Zheng Yifeng⁴^ORCID,Fu Anmin¹^ORCID,Zhou Pan⁵^ORCID,Abbott Derek²^ORCID,Al-Sarawi Said F.²^ORCID

Affiliation:

1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

2. School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia

3. Data61, CSIRO, Sydney, NSW, Australia

4. School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China

5. Hubei Engineering Research Center on Big Data Security, School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/43/10077488/09852785.pdf?arnumber=9852785

Reference59 articles.

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2. A continual learning survey: Defying forgetting in classification tasks;de lange;IEEE Trans Pattern Anal Mach Intell,2022

3. XNOR-Net++: Improved binary neural networks;bulat;Proc Brit Mach Vis Conf (BMVC),2019

4. Lightweight (Reverse) Fuzzy Extractor With Multiple Reference PUF Responses

5. XNOR Neural Engine: A Hardware Accelerator IP for 21.6-fJ/op Binary Neural Network Inference

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