Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …

Hyperspectral image (HSI) contains hundreds of adjacent spectral bands, which can
effectively differentiate the region of interest. Nevertheless, many irrelevant and highly …

As an effective manner to reduce data redundancy and processing inconvenience,
hyperspectral band selection aims to select a subset of informative and discriminative bands …

Band selection is an effective method to deal with the difficulties in image transmission,
storage, and processing caused by redundant and noisy bands in hyperspectral images …

Abstract Background and Objective Medical hyperspectral images (MHSIs) are used for a
contact-free examination of patients without harmful radiation. However, high-dimensionality …

Hyperspectral image (HSI) characteristics of the abundant spectral information are favored
by many scholars, but the challenge is how to select relevant features from such high …

Hyperspectral images (HSIs) provide rich spectral information, facilitating many applications,
including landcover classification. However, due to the high dimensionality of HSIs …

Scholars have performed much research on reducing the redundancy of hyperspectral data.
As a measure of the similarity between hyperspectral bands, structural similarity is used in …

Contextual situations, such as having dinner at a restaurant on Friday with the spouse,
became a useful mechanism to represent context in context-aware recommender systems …

Hyperspectral images (HSI) contain a great number of bands, which enable better
characterization of features. However, the huge dimension and information volume brought …