Convolutional NN for change detection
This project deals with the task of detecting relevant changes between two satellite images taken of the same scene at different times. A convolutional neural network (CNN) and semantic segmentation is implemented to detect the changes between the images, as well as classify the changes into the correct semantic class. A difference image is created using the feature maps generated by the CNN, which means that the CNN does not need to learn the non-linear mapping between two images and is thus unsupervised in the task of change detection.
Below is a diagram of the Unet architecture used in this project:
