A feature space class balancing strategy-based fault classification method in solar photovoltaic modules-Reference-Cited by-同舟云学术

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A feature space class balancing strategy-based fault classification method in solar photovoltaic modules

Published:2024-10 Issue: Volume:136 Page:108991
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wu Shizhen^ORCID,Kong Yaguang^ORCID,Xu Ruidong,Guo Yunfei,Chen Zhangping,Zheng Xiaoqing^ORCID

Funder

Zhejiang Province Basic Public Welfare Research Program

Key Research and Development Program of Zhejiang Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference57 articles.

1. Theoretical foundations of t-SNE for visualizing high-dimensional clustered data;Cai;J. Mach. Learn. Res.,2022

2. Improved YOLOv8-GD deep learning model for defect detection in electroluminescence images of solar photovoltaic modules;Cao;Eng. Appl. Artif. Intell.,2024

3. Learning imbalanced datasets with label-distribution-aware margin loss;Cao;Neural Inf. Process. Syst.,2019

4. A robust weakly supervised learning of deep Conv-Nets for surface defect inspection;Chen;Neural Comput. Appl.,2020

5. Fault diagnosis method for photovoltaic panels based on improved ShuffleNet V2 and infrared images;Chen,2022

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