Few-Shot Lightweight SqueezeNet Architecture for Induction Motor Fault Diagnosis Using Limited Thermal Image Dataset-Reference-Cited by-同舟云学术

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Few-Shot Lightweight SqueezeNet Architecture for Induction Motor Fault Diagnosis Using Limited Thermal Image Dataset

Published:2024 Issue: Volume:12 Page:50986-50997
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Siraj Farhan Md.¹^ORCID,Ayon Syed Tasnimul Karim¹^ORCID,Samad Md. Abdus²^ORCID,Uddin Jia³^ORCID,Choi Kwonhue²^ORCID

Affiliation:

1. Department of Computer Science and Engineering, BRAC University, Dhaka, Bangladesh

2. Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, Republic of Korea

3. Department of AI and Big Data, Endicott College, Woosong University, Daejeon, South Korea

Funder

2023 Yeungnam University Research Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10493002.pdf?arnumber=10493002

Reference48 articles.

1. Recent advances in intelligent fault diagnosis: A comprehensive review;Smith;J. Ind. Eng.,2020

2. Comparing offshore and onshore wind development considering acceptance costs

3. An Overview on Fault Diagnosis, Prognosis and Resilient Control for Wind Turbine Systems

4. Fault Diagnosis of Electric Motors Using Deep Learning Algorithms and Its Application: A Review

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine Fault Diagnosis: Experiments with Different Attention Mechanisms Using a Lightweight SqueezeNet Architecture;Electronics;2024-08-06

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