6533b7d1fe1ef96bd125ce44

RESEARCH PRODUCT

Convolutional Neural Network for Dust and Hotspot Classification in PV Modules

A. D'amicoGiovanni CiprianiMarzia TraversoVincenzo Di DioDonatella MannoStefania Guarino

subject

Control and OptimizationComputer science020209 energyReal-time computingEnergy Engineering and Power Technologydiagnosticconvolutional neural network02 engineering and technology010501 environmental sciencesSettore ING-IND/32 - Convertitori Macchine E Azionamenti Elettricilcsh:Technology01 natural sciencesConvolutional neural networkphotovoltaic energyhot spotHotspot (geology)diagnostics0202 electrical engineering electronic engineering information engineeringenergy efficientElectrical and Electronic EngineeringEngineering (miscellaneous)0105 earth and related environmental sciencesSettore ING-IND/11 - Fisica Tecnica Ambientalelcsh:TRenewable Energy Sustainability and the Environmentbusiness.industryPhotovoltaic systemDirtartificial intelligencerenewable energy620Renewable energyElectricity generationinfrared thermographydustddc:620businessEnergy (miscellaneous)Efficient energy use

description

20th IEEE International Conference on Environment and Electrical Engineering, EEEIC 2020, online, 9 Jun 2020 - 12 Jun 2020; Energies : open-access journal of related scientific research, technology development and studies in policy and management 13(23), 6357 (2020). doi:10.3390/en13236357 special issue: "Special Issue "Selected Papers from 20 IEEE International Conference on Environment and Electrical Engineering (EEEIC 2020)" / Special Issue Editor: Prof. Dr. Rodolfo Araneo, Guest Editor"

yearjournalcountryeditionlanguage
2020-12-02
10.3390/en13236357http://hdl.handle.net/10447/466959