Update README.md

README.md

@@ -1,6 +1,9 @@
-# Fault-Detection-System
+# Fault Detection System
+
 A repository for CNN based binary classification model for the task of detecting defective solar module cells.
 
+Developed by Cherifi Imane; ([Step by step documentation](https://iq.opengenus.org/fault-detection-system-predict-defective-solar-module-cells/))
+
 ## Execution
 All the codes have been run on Google Colab.
 The codes are coded in the python 3.x version
@@ -28,4 +31,4 @@ The models folder is where the best trained model will be saved
 
 [1] Buerhop-Lutz, C.; Deitsch, S.; Maier, A.; Gallwitz, F.; Berger, S.; Doll, B.; Hauch, J.; Camus, C. & Brabec, C. J. A Benchmark for Visual Identification of Defective Solar Cells in Electroluminescence Imagery. European PV Solar Energy Conference and Exhibition (EU PVSEC), 2018. DOI: 10.4229/35thEUPVSEC20182018-5CV.3.15
 
-[2] Deitsch, S., Buerhop-Lutz, C., Sovetkin, E., Steland, A., Maier, A., Gallwitz, F., & Riess, C. (2021). Segmentation of photovoltaic module cells in uncalibrated electroluminescence images. Machine Vision and Applications, 32(4). DOI: 10.1007/s00138-021-01191-9
+[2] Deitsch, S., Buerhop-Lutz, C., Sovetkin, E., Steland, A., Maier, A., Gallwitz, F., & Riess, C. (2021). Segmentation of photovoltaic module cells in uncalibrated electroluminescence images. Machine Vision and Applications, 32(4). DOI: 10.1007/s00138-021-01191-9