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Efficient Attentive U-Net for Fault Diagnosis and Predictive Maintenance of Photovoltaic Panels Through Infrared Thermography

Photovoltaic (PV) systems represent one of the pillars of the global energy transition, yet their reliability and long-term efficiency are constantly threatened by hidden defects and progressive degradation. Early and precise identification of such anomalies is essential for ensuring safety, enhanci...

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Principais autores: Danilo Pratticò, Filippo Laganà, Mario Versaci, Dubravko Franković, Alen Jakoplić, Fabio La Foresta
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2025-12-01
coleção:Energies
Assuntos:
photovoltaic systems
energy yield
infrared thermography
deep learning
CNN
U-Net
Acesso em linha:https://www.mdpi.com/1996-1073/18/24/6472
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