Replication Data for Remote Damage Detection of Power Plants using Deep Learning based drone image analysis

Replication Data for Remote Damage Detection of Power Plants using Deep Learning-based drone image analysis Thermal Solar, Large Solar, Small Solar, Wind turbine image dataset of drone inspection with damages annotated. Some of the images being collected from the following reference. Estefanía Alfaro-Mejía, Humberto Loaiza-Correa, Edinson Franco-Mejía, Andrés David Restrepo-Girón, Sandra Esperanza Nope-Rodríguez, Dataset for recognition of snail trails and hot spot failures in monocrystalline Si solar panels, Data in Brief, Volume 26, 2019, 104441, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2019.104441. S. Mehta, A. P. Azad, S. A. Chemmengath, V. Raykar, and S. Kalyanaraman, DeepSolarEye: Power Loss Prediction and Weakly Supervised Soiling Localization via Fully Convolutional Networks for Solar Panels," 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, NV, 2018, pp. 333-342. Shihavuddin, A.S.M., Chen, X., Fedorov, V., Nymark Christensen, A., Andre Brogaard Riis, N., Branner, K., Bjorholm Dahl, A. and Reinhold Paulsen, R., 2019. Wind turbine surface damage detection by deep learning aided drone inspection analysis. Energies, 12(4), p.676.