Implementation of the paper "SolNet: A Convolutional Neural Network for Detecting Dust on Solar Panels"
Authors:
Md. Saif Hassan Onim,
Zubayar Mahatab Md Sakif,
Adil Ahnaf,
Ahsan Kabir,
Rafina Afreen,
Sumaita Tanjim Hridy,
Mahtab Hossain,
Abul Kalam Azad,
Taskeed Jabid and
Md Sawkat Ali
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Get the dataset from here: Dataset
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Keep the dataset in the dataset folder. You can keep your own dataset for testing purpose.
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Run the 'train.py' from 'utils' folder to train the model
@Article{SolNet2022,
AUTHOR = {Onim, Md Saif Hassan and
Sakif, Zubayar Mahatab Md and
Ahnaf, Adil and
Kabir, Ahsan and
Azad, Abul Kalam and
Oo, Amanullah Maung Than and
Afreen, Rafina and
Hridy, Sumaita Tanjim and
Hossain, Mahtab and
Jabid, Taskeed and
Ali, Md Sawkat},
TITLE = {SolNet: A Convolutional Neural Network for Detecting Dust on Solar Panels},
JOURNAL = {Energies},
VOLUME = {16},
YEAR = {2023},
NUMBER = {1},
ARTICLE-NUMBER = {155},
URL = {https://www.mdpi.com/1996-1073/16/1/155},
ISSN = {1996-1073},
DOI = {10.3390/en16010155}
}
--The folder "dataset" will include the clean and dirty PV panel images to train a classification model from
--The folder "models" will contain models trained by the algorithm
--The folder "utils" contains scripts to train the classification model, where the file "train.py" is the mainfunction file and "model.py" is invoked by "model.py"