Hyperspectral band selection: A review
A hyperspectral imaging sensor collects detailed spectral responses from ground objects
using hundreds of narrow bands; this technology is used in many real-world applications …
using hundreds of narrow bands; this technology is used in many real-world applications …
[HTML][HTML] Strategies for dimensionality reduction in hyperspectral remote sensing: A comprehensive overview
The technological advancements in spectroscopy give rise to acquiring data about different
materials on earth's surface which can be utilized in a variety of potential applications. But …
materials on earth's surface which can be utilized in a variety of potential applications. But …
Chaotic gaining sharing knowledge-based optimization algorithm: an improved metaheuristic algorithm for feature selection
The gaining sharing knowledge based optimization algorithm (GSK) is recently developed
metaheuristic algorithm, which is based on how humans acquire and share knowledge …
metaheuristic algorithm, which is based on how humans acquire and share knowledge …
Gravitational search algorithm: a comprehensive analysis of recent variants
Gravitational search algorithm is a nature-inspired algorithm based on the mathematical
modelling of the Newton's law of gravity and motion. In a decade, researchers have …
modelling of the Newton's law of gravity and motion. In a decade, researchers have …
A feature selection approach for hyperspectral image based on modified ant lion optimizer
M Wang, C Wu, L Wang, D **ang, X Huang - Knowledge-Based Systems, 2019 - Elsevier
Feature selection is one of the most important issues in hyperspectral image (HSI)
classification to achieve high correlation between the adjacent bands. The main concern is …
classification to achieve high correlation between the adjacent bands. The main concern is …
Hyperspectral band selection using attention-based convolutional neural networks
Hyperspectral imaging has become a mature technology which brings exciting possibilities
in various domains, including satellite image analysis. However, the high dimensionality and …
in various domains, including satellite image analysis. However, the high dimensionality and …
A review of unsupervised band selection techniques: Land cover classification for hyperspectral earth observation data
A hyperspectral image (HSI) is a collection of several narrow-band images that span a wide
spectral range. Each band reflects the same scene, composed of various objects imaged at …
spectral range. Each band reflects the same scene, composed of various objects imaged at …
[HTML][HTML] Learning-based optimization of hyperspectral band selection for classification
Hyperspectral sensors acquire spectral responses from objects with a large number of
narrow spectral bands. The large volume of data may be costly in terms of storage and …
narrow spectral bands. The large volume of data may be costly in terms of storage and …
Unsupervised band selection of medical hyperspectral images guided by data gravitation and weak correlation
C Zhang, Z Zhang, D Yu, Q Cheng, S Shan, M Li… - Computer Methods and …, 2023 - Elsevier
Abstract Background and Objective Medical hyperspectral images (MHSIs) are used for a
contact-free examination of patients without harmful radiation. However, high-dimensionality …
contact-free examination of patients without harmful radiation. However, high-dimensionality …
Chaotic atom search optimization for feature selection
Due to the lack of experience and prior knowledge, the selection of the most informative
features has become one of the challenging problems in many applications. Recently, many …
features has become one of the challenging problems in many applications. Recently, many …