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Enhancing photovoltaic cell classification through mamdani fuzzy logic: a comparative study with machine learning approaches employing electroluminescence images.

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Title: Enhancing photovoltaic cell classification through mamdani fuzzy logic: a comparative study with machine learning approaches employing electroluminescence images.
Authors: Mateo-Romero, Hector Felipe1, hectorfelipe.mateo@uva.es, Carbonó de la Rosa, Mario Eduardo2, mecr@ier.unam.mx, Hernández-Callejo, Luis1, luis.hernandez.callejo@uva.es, González-Rebollo, Miguel Ángel1, mrebollo@eii.uva.es, Cardeñoso-Payo, Valentín1, valentin.cardenoso@uva.es, Alonso-Gómez, Victor1, victor.alonso.gomez@uva.es, Gallardo-Saavedra, Sara1, sara.gallardo@uva.es, Morales Aragonés, Jose Ignacio1, joseignacio.morales@uva.es
Source: Progress in Artificial Intelligence (2192-6352); Mar2025, Vol. 14 Issue 1, p49-59, 11p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 183374817
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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        Value: 10.1007/s13748-024-00353-w
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      – Code: eng
        Text: English
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        PageCount: 11
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      – TitleFull: Enhancing photovoltaic cell classification through mamdani fuzzy logic: a comparative study with machine learning approaches employing electroluminescence images.
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            NameFull: Mateo-Romero, Hector Felipe
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              M: 03
              Text: Mar2025
              Type: published
              Y: 2025
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              Value: 14
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