Results 41 to 50 of about 23,100 (259)
Optimal Clustering Framework for Hyperspectral Band Selection
, 2018 Band selection, by choosing a set of representative bands in hyperspectral image (HSI), is an effective method to reduce the redundant information without compromising the original contents. Recently, various unsupervised band selection methods have been
Li, Xuelong, Wang, Qi, Zhang, Fahong
core +1 more source
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
Non-convex regularization in remote sensing [PDF]
, 2016 In this paper, we study the effect of different regularizers and their implications in high dimensional image classification and sparse linear unmixing. Although kernelization or sparse methods are globally accepted solutions for processing data in high ...
Barlaud, Michel +2 more
core +4 more sources
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
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches [PDF]
, 2012 Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras.
Antonio Plaza +8 more
core +8 more sources
Advanced Functional Materials, EarlyView.Controlled syntheses of lanthanide coordination polymers based on the dihydroxybenzoquinone (DHBQ) organic linker afforded large single crystals of Ln‐DHBQ CPs (Ln = Yb, Nd). A novel structural variant of Yb‐DHBQ is identified by means of single crystal diffraction analysis.
Marina I. Schönherr +7 more
wiley +1 more source
Gradients in urban material composition: A new concept to map cities with spaceborne imaging spectroscopy data [PDF]
, 2019 To understand processes in urban environments, such as urban energy fluxes or surface temperature patterns, it is important to map urban surface materials. Airborne imaging spectroscopy data have been successfully used to identify urban surface materials
Feilhauer, Hannes +3 more
core +2 more sources
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Advanced Functional Materials, EarlyView.Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source
Explainability Feature Bands Adaptive Selection for Hyperspectral Image Classification
Remote SensingHyperspectral remote sensing images are widely used in resource exploration, urban planning, natural disaster assessment, and feature classification. Aiming at the problems of poor interpretability of feature classification algorithms for hyperspectral ...
Jirui Liu +5 more
doaj +1 more source
BAND SELECTION METHOD APPLIED TO M3 (MOON MINERALOGY MAPPER) [PDF]
, 2012 poster abstractRemote sensing optical sensors, such as those on board satellites and planetary probes, are able to detect and measure solar radiation at both im-proved spectral and spatial resolution. In particular, a hyperspectral dataset often consists
Cavanagh, Patrick D., Li, Lin
core