Defect Diagnosis of Photovoltaic Module Visible Light Images Under Imbalanced Sample Conditions

Defect Diagnosis of Photovoltaic Module Visible Light Images Under Imbalanced Sample Conditions

To address the issues of high miss and false detection rates in defect detection of PV (photovoltaic) module visible light images under imbalanced data conditions, an improved data augmentation method based on DCGAN (Deep Convolutional Generative Adversarial Networks) is proposed. Firstly, in the DC...

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Bibliographic Details
Main Authors: Huiqing Rao, Qiong Li, Long Chen, Sha Jin, Yong Lu, Zhiguang Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Photovoltaic module image
data generation
generate adversarial networks
imbalanced sample
Online Access:https://ieeexplore.ieee.org/document/11016723/
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https://ieeexplore.ieee.org/document/11016723/

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