Unsupervised Learning Implementation for SAR Images Clustering
Mostafa Elsaadouny, Jan Barowski, Ilona Rolfes · 2021
Unsupervised learning algorithms play a major role and participate in different applications. These algorithms work mainly on defining the hidden patterns within the dataset and clustering the data points into different groups. Unlike supervised learning, unsupervised learning works without any supervision from human, therefore, it is mainly used with unknown data to discover the underlying structure of it. In this research, two of the main unsupervised learning algorithms are implemented and evaluated in clustering of the synthetic aperture radar (SAR) images.