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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11016723/ |
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