Author:
Xie Xiangying,Liu Xinyue,Chen QiXiang,Leng Biao
Publisher
Springer Nature Singapore
Reference19 articles.
1. Anwar, S.A., Abdullah, M.Z.: Micro-crack detection of multicrystalline solar cells featuring an improved anisotropic diffusion filter and image segmentation technique. EURASIP J. Image Video Process. 2014, 1–17 (2014)
2. Buerhop-Lutz, C., et al.: A benchmark for visual identification of defective solar cells in electroluminescence imagery. In: 35th European PV Solar Energy Conference and Exhibition, vol. 12871289, pp. 1287–1289 (2018)
3. Deitsch, S., et al.: Segmentation of photovoltaic module cells in uncalibrated electroluminescence images. Mach. Vis. Appl. 32(4), 84 (2021)
4. Deitsch, S., et al.: Automatic classification of defective photovoltaic module cells in electroluminescence images. Sol. Energy 185, 455–468 (2019)
5. Demirci, M.Y., Beşli, N., Gümüşçü, A.: Efficient deep feature extraction and classification for identifying defective photovoltaic module cells in electroluminescence images. Expert Syst. Appl. 175, 114810 (2021)