Research work based on this database has been submitted to 'Electronics', and the manuscript is titled "GBH-YOLOv5: Ghost convolution with BottleneckCSP and tiny target prediction Head incorporating YOLOv5 for PV paneldefect detection"
@article{Li2023,
title = {GBH-YOLOv5: Ghost Convolution with BottleneckCSP and Tiny Target Prediction Head Incorporating YOLOv5 for PV Panel Defect Detection},
shorttitle = {GBH-YOLOv5},
author = {Li, Longlong and Wang, Zhifeng and Zhang, Tingting},
year = {2023},
month = jan,
journal = {Electronics},
volume = {12},
number = {3},
pages = {1--15},
publisher = {Multidisciplinary Digital Publishing Institute},
issn = {2079-9292},
doi = {10.3390/electronics12030561},
copyright = {http://creativecommons.org/licenses/by/3.0/},
}
The JPEGImages folder holds the image files and the Annotations folder holds the label files.
- Photovoltaic panels with broken areas.
- Photovoltaic panels have obvious bright spot areas.
- Photovoltaic panels with black or gray border areas.
- Photovoltaic panels with scratched areas.
- Photovoltaic panels have non-electricity and show black areas.
If you have any question about the Dataset, please feel free to contact us through zfwang@ccnu.edu.cn.