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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Hlavní autoři:	Huiqing Rao, Qiong Li, Long Chen, Sha Jin, Yong Lu, Zhiguang Li
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2025-01-01
Edice:	IEEE Access
Témata:	Photovoltaic module image data generation generate adversarial networks imbalanced sample
On-line přístup:	https://ieeexplore.ieee.org/document/11016723/
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