Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains ...

Feature selection is a critical pre-processing step in machine learning that seeks to identify a subset of input variables most relevant to predictive modelling. By reducing dimensionality, it ...

A team of computer engineering researchers in Iran has unveiled a new machine learning framework that combines federated learning, bio-inspired optimization, and deep neural networks to pick out the ...