Detection of Water-Bodies Using Semantic Segmentation

This paper proposes a semantic segmentation technique to automatically detect water-bodies from DubaiSat-2 images. The proposed method uses a deep convolutional neural network transfer-learning model. Several evaluation metrics such as accuracy, precision, and Jaccard coefficient are used to test our proposed algorithm. The overall accuracy for the prediction of water-bodies in DubaiSat-2 image dataset is 99.86%.