Supervised classification is a method that requires you to select training samples or areas of interest that represent the different land cover classes you want to identify. The algorithm then ...

This is an improved and more robust version of an unsupervised machine learning algorithm originally developed in Hocking et al. 2018 and Martin et al. 2020 involving several clustering and data size ...

Abstract: An integrated spatial-spectral information algorithm for hyper spectral image classification is proposed, which uses spatial pixel association (SPA)by exploiting spectral information ...

Now that you have a solid foundation in Supervised Learning, we shift our attention to uncovering the hidden structure from unlabeled data. We will start with an introduction to Unsupervised Learning.

Most of the unsupervised classification algorithms are based on clustering algorithms. Clustering algorithms find best suited natural groups within the given feature space. In this study, the sensor ...

Since their manifestation is a priori unknown, an unsupervised classification algorithm, making no prior assumptions regarding the data is clearly desirable. Here we present such an approach based ...