## Initially hyperspectral (HS) data exploitation model on identification of pure spectral signatures (endmembers) and their corresponding fractional abundances in each pixel of the HS data cube has been proposed.

Deep learning framework based on Spectral and Spatial properties for Land-Cover Classification using Landsat Hyperspectral Images

## Spectral unmixing is an important technique for hyperspectral image application, which aims to estimate the pure spectral signatures in each mixed pixel and their corresponding fractional abundances.

Low-Rank Subspace Unmixing of Remotely Sensed Hyperspectral Image

## Blind hyperspectral unmixing is an important technique in hyperspectral image analysis, aiming at estimating endmembers and their respective fractional abundances.

LSTM-DNN Based Autoencoder Network for Nonlinear Hyperspectral Image Unmixing

## The linear mixture model has been widely utilized to unmix hyperspectral images by extracting a set of pure spectral signatures, called endmembers in hyperspectral jargon, and estimating their respective fractional abundances in each pixel of the scene.

Multi-GPU Based Parallel Design of the Ant Colony Optimization Algorithm for Endmember Extraction from Hyperspectral Images

## Furthermore, a reweighted <inline-formula><tex-math notation="LaTeX">$\ell _1$</tex-math></inline-formula>-norm minimization scheme is adopted instead to enhance the sparsity of estimated fractional abundances.

Hypergraph Learning and Reweighted $\ell _1$-Norm Minimization for Hyperspectral Unmixing

## Then noise-adjusted principal component analysis (NAPCA) is taken to transform the original datasets into PCA domain and maintain only the most significant principal component as well as wipe off the inaccurate estimated fractional abundances.

Local Block Grouping with Napca Spatial Preprocessing for Hyperspectral Remote Sensing Imagery Sparse Unmixing

## Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs) are calculated within structural groups based on methylation number, methylation position, and cyclization number.

Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments

## Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs) are calculated within structural groups based on methylation number, methylation position, and cyclization number.

Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments

## Fractional abundances of methylated GSTP1 DNA fragments were significantly increased in subgroup III of metastatic PCa patients (p < 0.

Increased Sensitivity of Detection of RASSF1A and GSTP1 DNA Fragments in Serum of Prostate Cancer Patients: Optimisation of Diagnostics Using OBBPA-ddPCR

10.17762/TURCOMAT.V12I9.3564

## Initially hyperspectral (HS) data exploitation model on identification of pure spectral signatures (endmembers) and their corresponding fractional abundances in each pixel of the HS data cube has been proposed.

Deep learning framework based on Spectral and Spatial properties for Land-Cover Classification using Landsat Hyperspectral Images

## In addition, we identified several cell subsets whose fractional abundances associated with histological determined EE severity, small intestinal region, and HIV infection.

Single-cell profiling of environmental enteropathy reveals signatures of epithelial remodeling and immune activation in severe disease

10.1088/1757-899X/1084/1/012041

## Hyperspectral unmixing is the procedure by which the end component elements are calculated and their fractional abundances are found in each pixel in hyperspectral images.

Joint Sparsity and Total Variation Based Unmixing of Mixed Noise

## Blind hyperspectral unmixing is an important technique in hyperspectral image analysis, aiming at estimating endmembers and their respective fractional abundances.

LSTM-DNN Based Autoencoder Network for Nonlinear Hyperspectral Image Unmixing

## Fractional abundances of bauxite were derived by using a matched-filtering method.

Using reflectance spectroscopy and Advanced Spaceborne Thermal Emission and Reflection Radiometer data to identify bauxite deposits in vicinity of Az Zabirah, northern Saudi Arabia

## While gas-phase astrochemical reaction networks nicely replicate the abundance of hydrogen-deficient organics like linear cyanopolyynes, pathways to complex organic molecules (COMs)—organic molecules with six or more atoms—have not been completely understood, with gas-phase models often significantly underestimating fractional abundances of the astronomically observed organics by orders of magnitude.

Cyclopropenone (c-C3H2O) as a Tracer of the Nonequilibrium Chemistry Mediated by Galactic Cosmic Rays in Interstellar Ices

10.5194/egusphere-egu21-8362

## We use the compiled dataset and new fractional abundances to generate brGDGT calibrations for warm-season air temperatures and lake water conductivity and pH for use in lake sediments globally.

Revised brGDGT fractional abundances and warm-season temperatures strengthen relationships between brGDGTs and environmental variables

10.1051/0004-6361/202140655

## The fractional abundances of HCNH+ with respect to H2, [HCNH+], are in the range 0.

First survey of HCNH+ in high-mass star-forming cloud cores

## The 13C- and 12C-isotopologues of the amino acid phenylalanine (Phe) proved to be a quantitatively accurate reporter molecules of cellular isotopic fractional abundances (fcell).

Using Stable Isotope Probing and Raman Microspectroscopy to measure growth rates of heterotrophic bacteria.

## Spectral unmixing is an important technique for hyperspectral image application, which aims to estimate the pure spectral signatures in each mixed pixel and their corresponding fractional abundances.

Low-Rank Subspace Unmixing of Remotely Sensed Hyperspectral Image

10.1103/PhysRevD.103.083512

## In all cases we evaluate the fractional abundances of PBHs by comparing Press–Schechter approach and peak theory, while focusing on explaining the dark matter in the Universe.

Mechanisms of producing primordial black holes by breaking the SU(2, 1)/SU(2)×U(1) symmetry

## It amounts at estimating the spectral signatures of the pure spectral constituents in the scene (endmembers) and their corresponding subpixel fractional abundances.

Deep Autoencoders With Multitask Learning for Bilinear Hyperspectral Unmixing

10.5194/EGUSPHERE-EGU21-4542

## This indicates that the mechanism behind the changed fractional abundances is a pH-modulated bacterial community shift.

Testing a thermometer of the past: abiotic and biotic drivers of the brGDGT-based temperature proxy along a subarctic elevation gradient.

## Due to the complex interaction of light with mixed materials, reflectance spectra are highly nonlinearly related to the pure material endmember spectra, making it hard to estimate the fractional abundances of the materials.

Robust Supervised Method for Nonlinear Spectral Unmixing Accounting for Endmember Variability

10.1101/2021.01.26.21250013

## KRAS mutant droplets were detected in three out of nine platelet RNA samples with fractional abundances of 0.

Detecting therapy-guiding RNA aberrations in platelets of non-small cell lung cancer patients

10.1051/0004-6361/202140667

## Recent water line observations toward several low-mass protostars suggest low water gas fractional abundances (< 10−6 with respect total hydrogen density) in the inner warm envelopes (r < 102 au).

X-ray-induced chemistry of water and related molecules in low-mass protostellar envelopes

## Meanwhile, the spectral-spatial weighted sparse regularization term is introduced to promote the sparsity of fractional abundances in the spectral and spatial domains.

Superpixel Based Low-Rank Sparse Unmixing for Hyperspectral Remote Sensing Image

## These candidates present small velocity dispersions, high fractional abundances of NH2D, high NH3 deuterium fractionations, and are completely dark in the infrared wavelengths from 3.

A Low-mass Cold and Quiescent Core Population in a Massive Star Protocluster

10.36227/techrxiv.16831330.v1

## We also adopt a double reweighted $\ell_{1}$ norm minimization scheme to promote the sparsity of fractional abundances.

Pointwise Mutual Information based Graph Laplacian Regularized Sparse Unmixing

## The proposed deep image prior uses a convolutional neural network to estimate the fractional abundances, relying on the extracted endmembers and the observed hyperspectral dataset.

Spectral Unmixing Using Deep Convolutional Encoder-Decoder

## Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs) are calculated within structural groups based on methylation number, methylation position, and cyclization number.

Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments

## The proposed deep image prior uses a convolutional neural network to estimate the fractional abundances, relying on the extracted endmembers and the observed hyperspectral data set.

UnDIP: Hyperspectral Unmixing Using Deep Image Prior

## , endmembers and their associated fractional abundances, to retrieve hyperspectral scenes.

A Parallel Unmixing-Based Content Retrieval System for Distributed Hyperspectral Imagery Repository on Cloud Computing Platforms

10.1080/01431161.2021.1958390

## ABSTRACT Blind hyperspectral unmixing is a key technique for mixing spectral analysis, which separate the endmember spectra from hyperspectral image and evaluate their fractional abundances.

A Local Similarity Driven Model for Blind Hyperspectral Unmixing with Spectral Variability

## We also adopt a double reweighted $\ell_{1}$ norm minimization scheme to promote the sparsity of fractional abundances.

Pointwise Mutual Information based Graph Laplacian Regularized Sparse Unmixing

## Their fractional abundances exhibited differences beyond the sample temperature.

From Energetics to Intracluster Chemistry: Valence Photoionization of Trifluoromethylsulfur Pentafluoride (CF3SF5) by Double Velocity Map Imaging.

10.1051/0004-6361/202141573

## We have obtained molecular fractional abundances with respect to H$_{2}$ from 10$^{-7}$ down to a few 10$^{-9}$ and with respect to CH$_{3}$OH from 10$^{-3}$ to $\sim$4$\times$10$^{-2}$.

The GUAPOS project. II. A comprehensive study of peptide-like bond molecules

10.1080/01431161.2021.1933245

## ABSTRACT Nonnegative matrix factorization (NMF) has been one of the most widely used techniques for hyperspectral unmixing (HU), which aims at decomposing each mixed pixel into a set of endmembers and their corresponding fractional abundances.

Nonnegative matrix factorization with entropy regularization for hyperspectral unmixing

## Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs) are calculated within structural groups based on methylation number, methylation position, and cyclization number.

Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments

## In this work, we present a nonlinear spectral mixing model that, apart from the fractional abundances, contains two additional parameters, one accounting for multiple reflections and another accounting for shadow.

A Spectral Mixing Model Accounting for Multiple Reflections and Shadow

## In a first step, we propose to use sparse fractional abundances as decision source, complementary to class probabilities obtained from a supervised classifier.

Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields

## Hyperspectral unmixing is the process of finding the fractional abundances and corresponding spectral signatures of a mixed pixel in a hyperspectral image.

Robust Hyperspectral Unmixing Using Total Variation Regularized Low-Rank Approximation

10.1051/0004-6361/201936536

## Finally, from our application to L1157, we find that the fractional abundances within the B2 region are consistent with both C-type and J-type shock emission.

Tracing shock type with chemical diagnostics: an application to L1157

## The physical and chemical conditions, such as density, temperature, and fractional abundances are calculated.

ALMA Observations of the Massive Molecular Outflow G331.512-0.103. II. Physical Properties, Kinematics, and Geometry Modeling

10.23883/ijrter.conf.20190304.005.rclxe

## It is the process of estimating constituent endmembers and their fractional abundances present at each pixel in a hyperspectral image.

SPECTRAL UNMIXING BASED ON JOINT SPARSITY AND TOTAL VARIATION USING REMOTE SENSING DATA

## We update the calibration of [NeII] and [NeIII] strength as a SFR indicator, explicitly considering the effects of metallicity, finding very good relations between Ne fractional abundances and the [NeIII]/[NeII] ratio for different metallicities, ionization parameters, and starburst ages.

A New Method to Measure Star Formation Rates in Active Galaxies Using Mid-infrared Neon Emission Lines

10.1504/ijcat.2019.10023596

## Linear Spectral Unmixing (LSU) is a widely used technique in the field of Remote Sensing (RS) for the estimation of fractional abundances of endmembers and their spectral signatures.

Collaborative sparse unmixing using variable splitting and augmented Lagrangian with total variation

10.1109/ACCESS.2019.2943110

## It aims at estimating the fractional abundances of pure spectral signatures in mixed pixels in hyperspectral images.

Joint-Sparse-Blocks Regression for Total Variation Regularized Hyperspectral Unmixing

## However, small fractional abundances were observed below 3000 m a.

Aircraft-based observation of meteoric material in lower stratospheric aerosol particles between 15 and 68°N

10.1051/0004-6361/201935354

## The C-S bearing species C2S and o-H2CS present fractional abundances a factor of > two higher in the core than in the PDR.

Abundances of sulphur molecules in the Horsehead nebula First NS+ detection in a photodissociation region.

10.1051/0004-6361/201935069

## We performed excitation and radiative transfer calculations based on the large velocity gradient (LVG) method to model the observed lines of the molecules and to derive their fractional abundances in the observed envelopes.

Study of CS, SiO, and SiS abundances in carbon star envelopes: Assessing their role as gas-phase precursors of dust.

## The column densities and fractional abundances of these species are measured and together these species account for 10\% of the cosmic sulfur abundance in the region.

Sulfur Chemistry in L1157-B1

10.1109/JSTARS.2019.2934011

## It comprises the identification of pure spectral signatures (endmembers) and their corresponding fractional abundances in each pixel of the HS data cube.

GPU Parallel Implementation of Dual-Depth Sparse Probabilistic Latent Semantic Analysis for Hyperspectral Unmixing

10.1109/WHISPERS.2019.8920893

## The mechanical and chemical properties of a compound material are determined by the fractional abundances of its components.

Fractional Abundance Estimation of Mixed and Compound Materials by Hyperspectral Imaging.

## The fragment ion fractional abundances, plotted in the breakdown diagram, along with the time-of-flight mass spectra for the first three metastable CO-loss channels were modeled using a statistical approach.

Dissociative photoionization of chromium hexacarbonyl: A round-trip ticket to non-statisticality and a detective story in thermochemistry

## The importance of the Hall effect varies with the Hall coefficient, and this coefficient is determined by the fractional abundances of charged species.

Dependence of Hall coefficient on grain size and cosmic ray rate and implication for circumstellar disc formation

## Production of simple and complex molecules to depth on the order of 10 m or more is achieved, with local fractional abundances comparable to observed values in many cases.

Simulations of ice chemistry in cometary nuclei.

## The linear mixture model has been widely utilized to unmix hyperspectral images by extracting a set of pure spectral signatures, called endmembers in hyperspectral jargon, and estimating their respective fractional abundances in each pixel of the scene.

Multi-GPU Based Parallel Design of the Ant Colony Optimization Algorithm for Endmember Extraction from Hyperspectral Images

10.1109/ACCESS.2019.2955984

## This method factorizes a hyperspectral cube into constituent endmembers and their fractional abundances.

Enhancing Hyperspectral Unmixing With Two-Stage Multiplicative Update Nonnegative Matrix Factorization

## Moreover, a computational framework based on spectral unmixing for the estimation of fractional abundances of oil palm plantations is proposed in this study.

Spectral unmixing approach in hyperspectral remote sensing: a tool for oil palm mapping

## Hyperspectral unmixing, by extracting the fractional abundances of endmembers from the hyperspectral image (HSI), has raised wide attention in recent years.

Hyperspectral Unmixing VIA L1/4 Sparsity-Constrained Multilayer NMF

## By considering the fact that adjacent pixels own not only the endmembers with same variations but also approximated fractional abundances, in this paper, local spectral similarity preserving (LSSP) constraint is proposed to preserve spectral similarity in a local area during robust sparse unmixing (RSU).

Local Spectral Similarity Preserving Regularized Robust Sparse Hyperspectral Unmixing

## Blind hyperspectral unmixing (HU), as a crucial technique for hyperspectral data exploitation, aims to decompose mixed pixels into a collection of constituent materials weighted by the corresponding fractional abundances.

Nonconvex-Sparsity and Nonlocal-Smoothness-Based Blind Hyperspectral Unmixing

## Although, the fractional abundances of individual components of NPK may be considered as future scope of work.

Soil fertility status assessment using hyperspectral remote sensing

## The proposed method enhances the sparsity of abundance factions in both the spectral sparsity (column sparsity of the fractional abundances in the sense) and the spatial sparsity (row sparsity of the fractional abundances in the sense).

Hyperspectral unmixing using double reweighted collaborative sparse regression

10.1051/0004-6361/201834654

## 3 cm and 7 mm) to determine the fractional abundances of CO, HCO+, HCN, CS, SO, HCS+, and N2H+ in three cuts which intersect the dense filament at the well-known positions TMC 1-CP, TMC 1-NH3, and TMC 1-C, covering a visual extinction range from A V ~ 3 to ~20 mag.

Gas phase Elemental abundances in Molecular cloudS (GEMS): I. The prototypical dark cloud TMC 1.

## We have compared line profiles and fractional abundances of PN and SiO, a typical shock tracer, and found that almost all objects detected in PN have high-velocity SiO wings.

Origin of the PN molecule in star-forming regions: the enlarged sample

## The labeling pattern or mass distribution vector describes the fractional abundances of all isotopologs with different masses as a result of isotopic labeling, which are typically resolved using mass spectrometry.

ElemCor: accurate data analysis and enrichment calculation for high-resolution LC-MS stable isotope labeling experiments

10.1109/JSTARS.2019.2916058

## Furthermore, a reweighted <inline-formula><tex-math notation="LaTeX">$\ell _1$</tex-math></inline-formula>-norm minimization scheme is adopted instead to enhance the sparsity of estimated fractional abundances.

Hypergraph Learning and Reweighted $\ell _1$-Norm Minimization for Hyperspectral Unmixing

## Hence, the bacterial fractional abundances in co-culture experiments—pairwise outcomes—are influenced by interspecies interactions.

Interspecies bacterial competition determines community assembly in the C. elegans intestine

## Second, we calculated landscape attributes including its compositions in 1992 and 2015, magnitude of pattern change, categories transition matrix for detailed characterization of change, fractional abundances of plant functional types (PFTs) in 1992 and 2015, and change trend type – a simple, overall descriptor of the character of landscape change.

Global assessment and mapping of changes in mesoscale landscapes: 1992-2015

10.1051/0004-6361/201834717

## We aim to characterise their spatial distribution and determine their fractional abundances mainly through radiative transfer and chemical modelling.

IRC+10216 mass loss properties through the study of $\lambda$3mm emission: Large spatial scale distribution of SiO, SiS, and CS

## Spectral unmixing aims at identifying the endmembers and their fractional abundances in the mixed pixels.

Deep Unfolded Iterative Shrinkage-Thresholding Model for Hyperspectral Unmixing

10.1109/ICASSP.2019.8683155

## Afterwards, we solve a matrix-factorization problem to estimate the fractional abundances using the variability scaling factors estimated in the previous step, what leads to a significantly more well-posed problem.

Improved Hyperspectral Unmixing with Endmember Variability Parametrized Using an Interpolated Scaling Tensor

## Spectral unmixing is a technique for remotely sensed image interpretation that expresses each (possibly mixed) pixel as a combination of pure spectral signatures (endmembers) and their fractional abundances.

DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing

## Moreover, most models lack a proper interpretation of the estimated parameters in terms of fractional abundances.

A Semi-Supervised Method for Nonlinear Hyperspectral Unmixing

## Then noise-adjusted principal component analysis (NAPCA) is taken to transform the original datasets into PCA domain and maintain only the most significant principal component as well as wipe off the inaccurate estimated fractional abundances.

Local Block Grouping with Napca Spatial Preprocessing for Hyperspectral Remote Sensing Imagery Sparse Unmixing

## Hyperspectral unmixing has been widely used to decompose a mixed pixel into a collection of endmembers weighted by their corresponding fractional abundances, in which endmember extraction step is of crucial importance.

Local Sparse Representation Based Spatial Preprocessing For Endmember Extraction