Results 51 to 60 of about 6,341 (223)
Spectral-Spatial Offset Graph Convolutional Networks for Hyperspectral Image Classification
, 2021 In hyperspectral image (HSI) classification, convolutional neural networks (CNN) have been attracting increasing attention because of their ability to represent spectral-spatial features.
Minghua Zhang +4 more
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Fusion technology has been the core strategy to obtain a high-spatial-spectral resolution hyperspectral image (HSI). In recent years, few fusion models focused on exploiting the underlying manifold structure in the spatial dimension of the high ...
Jiawei Jiang +4 more
doaj +1 more source
Age prediction of hematoma using hyperspectral imaging (HSI)
Forensic Science, Medicine and PathologyAbstract Hyperspectral imaging (HSI) analyzes the reflected light spectrum of an object, providing insights into its material composition. In this experimental, prospective study, standardized hematomas were created in subjects and observed over 21 days using a portable hyperspectral camera, aiming to correlate changes in the ...
S. Al-Arami +3 more
openaire +2 more sources
Hyperspectral Image Restoration with Self-supervised Learning: A Two-stage Training Approach
, 2021 Hyperspectral image (HSI) denoising is a crucial preprocessing task to improve the performance of the subsequent HSI interpretation and applications.
Chen, L, Zhou, J, Zhu, H, Qian, Y
core +1 more source
Singular spectrum analysis for effective feature extraction in hyperspectral imaging
, 2014 As a very recent technique for time series analysis, Singular Spectrum Analysis (SSA) has been applied in many diverse areas, where an original 1D signal can be decomposed into a sum of components including varying trends, oscillations and noise ...
Zabalza, Jaime +4 more
core +1 more source
Effective feature extraction and data reduction with hyperspectral imaging in remote sensing
, 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
Remote Sensing, 2022 In recent years, convolutional neural networks (CNNs) have been widely used in hyperspectral image (HSI) classification. However, feature extraction on hyperspectral data still faces numerous challenges.
Jun Sun +6 more
doaj +1 more source
Micromachined Double‐Membrane Mechanically Tunable Metamaterial for Thermal Infrared Filtering
Advanced Photonics Research, Volume 6, Issue 5, May 2025.Herein, a mechanically tunable double‐layer plasmonic metamaterial leveraging the extraordinary optical transmission effect observed in subwavelength arrays of openings within thin metal layers is presented. The concept is experimentally validated by integrating the proposed metamaterial structure into an electrostatic parallel‐plate actuator to create
Oleg Bannik +7 more
wiley +1 more source
Deep Parameterized Neural Networks for Hyperspectral Image Denoising
, 2023 Sparse representation (SR)-based hyperspectral image (HSI) denoising methods normally average the local denoising results of multiple overlapped cubes to recover the whole HSI.
Jiantao Zhou +8 more
core +1 more source
ICTACT Journal on Image and Video Processing, 2022 Hyperspectral images (HSI) have a wide range of spectral information compared to conventional images. This rich spectral information leads to store more information about the image.
K Priya, K K Rajkumar
doaj +1 more source