Unsupervised defect detection for solar photovoltaic cells based on convolutional autoencoder

Solar photovoltaic (PV) cells are inevitably subject to defects during the production process, affecting their power generation efficiency and life. Electroluminescence (EL) imaging is the mainstream non-destructive method for PV cell defect detection. Aiming at PV cell EL images, an unsupervised de...

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Vydané v:	Nondestructive testing and evaluation Ročník 40; číslo 12; s. 6143 - 6159
Hlavní autori:	Zhang, Yufei, Zhang, Xu, Tu, Dawei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Taylor & Francis 02.12.2025 Taylor & Francis Ltd
Predmet:	convolutional autoencoder Defect detection Defects Nondestructive testing Perception Performance measurement Photovoltaic cells PV cell Solar cells unsupervised learning
ISSN:	1058-9759, 1477-2671
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