Estimating Redundancy-Reliability of CNNs Based on Strip-Median Attributes-Reference-Cited by-同舟云学术

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Estimating Redundancy-Reliability of CNNs Based on Strip-Median Attributes

Published:2023-10 Issue:10 Volume:31 Page:1486-1496
ISSN:1063-8210
Container-title:IEEE Transactions on Very Large Scale Integration (VLSI) Systems
language:
Short-container-title:IEEE Trans. VLSI Syst.

Author:

Xiao Jie¹^ORCID,Yang Yujian¹,Long Haixia¹,Qin Rongzhen²^ORCID,Lou Jungang²^ORCID

Affiliation:

1. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China

2. Yangtze Delta Region (Huzhou) Institute of Intelligent Transportation and the Key Laboratory of Smart Management and Application of Modern Agricultural Resources, Huzhou University, Huzhou, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Primary Research and Development Plan of Zhejiang Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Link

http://xplorestaging.ieee.org/ielx7/92/10261320/10214423.pdf?arnumber=10214423

Reference38 articles.

1. MindFI: A Fault Injection Tool for Reliability Assessment of MindSpore Applicacions

2. EfficientNet: Rethinking model scaling for convolutional neural networks;tan;Proc Int Conf Mach Learn,2019

3. A Reliability Study on CNNs for Critical Embedded Systems

4. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size;iandola;arXiv 1602 07360,2016

5. Ares: A framework for quantifying the resilience of deep neural networks

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