Results 31 to 40 of about 12,054 (243)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingBand selection (BS) is an effective dimensionality reduction technique for hyperspectral images. Although many relevant methods have been proposed, they often only focus on the bandwise information and the correlation between the bands, and few of them ...
Wenxian Zhang +3 more
doaj +2 more sources
Sparsity Regularized Deep Subspace Clustering for Multicriterion-Based Hyperspectral Band Selection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral images provide rich spectral information corresponding to visible and near-infrared imaging regions, facilitating accurate classification, object identification, and target detection. However, the high volume of data creates a computational
Samiran Das +3 more
doaj +1 more source
Constrained-Target Band Selection With Subspace Partition for Hyperspectral Target Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral target detection is widely used in both military and civilian fields. In practical applications, how to select a low-correlation and representative band subset to reduce redundancy is worth discussing.
Xudong Sun +4 more
doaj +1 more source
Efficient Graph Convolutional Self-Representation for Band Selection of Hyperspectral Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Hyperspectral image (HSI) band selection (BS) is an important task for HSI dimensionality reduction, whose goal is to select an informative band subset containing less redundancy.
Yaoming Cai +3 more
doaj +1 more source
Non-Parametric Spatial Spectral Band Selection methods [PDF]
, 2021 © Cranfield University 2021. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright ownerThis project is about the development of band selection (BS) techniques for better target detection ...
Torres, Ruben M
core
, 2020 With hundreds of spectral bands, the rise of the issue of dimensionality in the classification of hyperspectral images is usually inevitable. In this paper, a restrictive polymorphic ant colony algorithm (RPACA) based band selection algorithm (RPACA-BS ...
Wu, P +6 more
core +1 more source
Hyperspectral imaging-based prediction of soluble sugar content in Chinese chestnuts
Frontiers in Forests and Global Change, 2023 Soluble sugars are critical determinants of fruit quality and play a significant role in human nutrition. Chestnuts, rich in soluble sugars, derive their sweetness from them.
Jinhui Yang +3 more
doaj +1 more source
Crop Classification for Agricultural Applications in Hyperspectral Remote Sensing Images
Applied Sciences, 2022 Hyperspectral imaging (HSI), measuring the reflectance over visible (VIS), near-infrared (NIR), and shortwave infrared wavelengths (SWIR), has empowered the task of classification and can be useful in a variety of application areas like agriculture, even
Loganathan Agilandeeswari +4 more
doaj +1 more source
Discovering the Representative Subset with Low Redundancy for Hyperspectral Feature Selection
Remote Sensing, 2019 In this paper, a novel unsupervised band selection (BS) criterion based on maximizing representativeness and minimizing redundancy (MRMR) is proposed for selecting a set of informative bands to represent the whole hyperspectral image cube.
Wenqiang Zhang +2 more
doaj +1 more source
The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers
Molecular Oncology, EarlyView.The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce +11 more
wiley +1 more source