Deep learning in defects detection of PV modules: A review
Identifying defects in photovoltaic (PV) modules is essential for ensuring optimal performance and prolonging their operational lifespan. Traditional manual inspection methods are time-consuming, labor-intensive, and subject to human error, necessitating the development of automated, efficient detec...
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Main Authors: | Katleho Masita, Ali Hasan, Thokozani Shongwe, Hasan Abu Hilal |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
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Series: | Solar Energy Advances |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2667113125000038 |
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