Spectral clustering is quite complex, but it can reveal patterns in data that aren't revealed by other clustering techniques. Data clustering is the process of grouping data items so that similar ...

Hyperspectral image classification is a challenging task due to the lack of ground-truth labels and high dimensionality of spectral bands. For hyperspectral image (HSI) data of cultural heritage ...

Spectral graph theory examines the structural and dynamical properties of graphs by analysing the spectra of associated matrices such as the adjacency matrix, Laplacian, normalised Laplacian and ...

Motif-based graph local clustering is a popular method for graph mining tasks due to its various applications, such as community detection, network optimization and graph learning. However, the ...

A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has ...