Lightweight Edge-side Fault Diagnosis Based on Knowledge Distillation-Reference-Cited by-同舟云学术

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Lightweight Edge-side Fault Diagnosis Based on Knowledge Distillation

Published:2022-07-08 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 14th International Conference on Advanced Infocomm Technology (ICAIT)
language:
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Author:

Shang Yingjun¹,Feng Tao²,Huo Yonghua¹,Duan Yongcun¹,Long Yuhan³

Affiliation:

1. Science and Technology on Communication Networks Laboratory The 54th Research Institute of CETC,Shijiazhuang,China

2. National Key Laboratory of Science and Technology on Information System Security Institute of System Engineering Chinese Academy of Military Science,Beijing,China

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

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9862527/9862604/09862734.pdf?arnumber=9862734

Reference11 articles.

1. Distilling the Knowledge in a Neural Network;hinton;Computer Science,2015

2. Research on edge computing technology for intelligent sensing layer of energy interconnection[J];shuhua;Electric Power Information and Communication Technology,2020

3. Directional PCA for Fast Detection and Accurate Diagnosis: A Unified Framework

4. LEFE-Net: A Lightweight Efficient Feature Extraction Network With Strong Robustness for Bearing Fault Diagnosis

5. Fault Diagnosis of Tennessee Eastman Process Based on Static PCA

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