Results 71 to 80 of about 309,259 (214)
Multiscale four‐dimensional imaging of cardiac remodelling after myocardial infarction
The Journal of Physiology, EarlyView.Abstract figure legend Multiscale 4D imaging framework for integrated phenotyping of post‐infarction remodelling. Myocardial infarction triggers dynamic changes across mechanical, haemodynamic and biological axes, progressing from acute injury and inflammation to extracellular matrix remodelling and scar maturation.
Hanzhou Lei, Boris Martinac, Yang Guo
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Remote Sensing, 2017 In this paper, a new method is presented for spatial resolution enhancement of hyperspectral images (HSI) using spectral unmixing and a Bayesian sparse representation.
Elham Kordi Ghasrodashti +3 more
doaj +1 more source
Magnetic Resonance in Medicine, Volume 96, Issue 6, Page 2615-2628, December 2026.ABSTRACT Purpose To extend localized quadratic (LQ) RF encoded spin‐echo imaging with acquisition and reconstruction strategies that improve efficiency and artifact robustness, positioning it as a practical alternative to 3D FSE for high‐resolution volumetric brain MRI.
Guruprasad Krishnamoorthy +2 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn recent years, hyperspectral sparse unmixing (HSU) has garnered extensive research and attention due to its unique characteristic of not requiring the estimation of endmembers and their number.
Kewen Qu +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Hyperspectral unmixing (HSU) is an important technique of remote sensing, which estimates the fractional abundances and the mixing matrix of endmembers in each mixed pixel from the hyperspectral image.
Yuan Yuan, Zihan Zhang, Qi Wang
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Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe +3 more
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Abundance Estimation Methods in Spectral Unmixing for Real Data [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesSpectral unmixing estimates the fractional abundances of materials, having associated spectra called endmembers, in pixels acquired by imaging spectrometers.
D. Cerra, M. Pato, E. Carmona
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Unmixing of Hyperspectral Data Using Spectral Libraries
International Journal of Environment and Geoinformatics, 2020 In hyperspectral images, pixels are found as a mixture of the spectral signatures of several materials, especially when there is an insufficient spatial resolution.
Sefa Küçük, Seniha Esen Yüksel
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Hyperspectral Images Unmixing Based on Abundance Constrained Multi-Layer KNMF
IEEE Access, 2021 Due to the low spatial resolution of the sensors, the hyperspectral images contain mixed pixels. The purpose of hyperspectral unmixing is to decompose the mixed pixels into a series of endmembers and abundance fractions.
Jing Liu, You Zhang, Yi Liu, Caihong Mu
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A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
Advanced Engineering Materials, Volume 28, Issue 20, 21 October 2026.High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source