Results 51 to 60 of about 5,679 (259)
Attention Networks for Band Weighting and Selection in Hyperspectral Remote Sensing Image Classification [PDF]
, 2019 Hyperspectral imaging is widely used in remote sensing because of its capability to capture the detailed spectral reflection of the ground object. The acquired rich band information brings significant benefits to better discriminate the target pixels ...
Wang, J, Huang, W, Zhou, J, Chen, JF
core +1 more source
Unsupervised Cluster-Wise Hyperspectral Band Selection for Classification
Remote Sensing, 2022 A hyperspectral image provides fine details about the scene under analysis, due to its multiple bands. However, the resulting high dimensionality in the feature space may render a classification task unreliable, mainly due to overfitting and the Hughes ...
Mateus Habermann +2 more
doaj +1 more source
Effective feature extraction and data reduction with hyperspectral imaging in remote sensing [PDF]
, 2014 Although PCA has been widely used for feature extraction and data reduction, it suffers from three main drawbacks: high computational cost, large memory requirement and low efficacy in processing large datasets such as HSI.
Zabalza, Jaime +3 more
core +1 more source
A comparative analysis of band selection techniques for hyperspectral image classification [PDF]
, 2019 Finding an optimal subspace of bands that has the most expressive power for classifying hyperspectral image has been very challenging task due to its insufficient number of training pixels with respect to large number of bands.
Hasan, MAM +3 more
core +1 more source
Two-Stage Unsupervised Hyperspectral Band Selection Based on Deep Reinforcement Learning
Remote SensingHyperspectral images are high-dimensional data that capture detailed spectral information across a wide range of wavelengths, enabling the precise identification and analysis of different materials or objects. However, the high dimensionality of the data
Yi Guo +4 more
doaj +1 more source
Advanced Functional Materials, EarlyView.In this work, we highlight a unique material platform capable of producing three distinct room temperature (RT) photoluminescence (PL) resonances from spatially separated regions composed of a heterobilayer (HBL), a homobilayer (HoBL), and an heterotrilayer (HTL) transition metal dichalcogenide (TMD) heterostructures configuration on a highly ...
Bhabani Sankar Sahoo +8 more
wiley +1 more source
Classification techniques for hyperspectral remote sensing [PDF]
, 2011 This study concerns with classification techniques in high dimensional space such as that of Hyperspectral Imaging (HSI) data sets, with objectives of understanding the strength and weakness of various classifiers and at the same time to study how ...
Kam, Firmin
core
Remote Sensing, 2022 Band subset selection (BSS) is one of the ways to implement band selection (BS) for a hyperspectral image (HSI). Different from conventional BS methods, which select bands one by one, BSS selects a band subset each time and preserves the best one from ...
Keng-Hao Liu +2 more
doaj +1 more source
Advanced Materials, EarlyView.AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Opportunities of Semiconducting Oxide Nanostructures as Advanced Luminescent Materials in Photonics
Advanced Materials, EarlyView.The review discusses the challenges of wide and ultrawide bandgap semiconducting oxides as a suitable material platform for photonics. They offer great versatility in terms of tuning microstructure, native defects, doping, anisotropy, and micro‐ and nano‐structuring. The review focuses on their light emission, light‐confinement in optical cavities, and
Ana Cremades +7 more
wiley +1 more source