Photovoltaic cell defect classification based on integration of residual-inception network and spatial pyramid pooling in electroluminescence images-Reference-Cited by-同舟云学术

Photovoltaic cell defect classification based on integration of residual-inception network and spatial pyramid pooling in electroluminescence images

Published:2023-11 Issue: Volume:229 Page:120546
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Acikgoz Hakan^ORCID,Korkmaz Deniz^ORCID,Budak Umit^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference38 articles.

1. Automatic classification of defective photovoltaic module cells in electroluminescence images with convolutional neural network;Acikgoz;Fırat University Journal of Engineering Science,2022

2. CNN based automatic detection of photovoltaic cell defects in electroluminescence images;Akram;Energy,2019

3. Machine learning based identification and classification of field-operation caused solar panel failures observed in electroluminescence images;Bordihn;IEEE Journal of Photovoltaics,2022

4. Convolutional neural network for dust and hotspot classification in PV modules;Cipriani;Energies,2020

5. Automatic classification of defective photovoltaic module cells in electroluminescence images;Deitsch;Solar Energy,2019

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