Search results for "Database normalization"

showing 2 items of 2 documents

Multiple Cost Functions and Regularization Options for Improved Retrieval of Leaf Chlorophyll Content and LAI through Inversion of the PROSAIL Model

2013

Abstract: Lookup-table (LUT)-based radiative transfer model inversion is considered a physically-sound and robust method to retrieve biophysical parameters from Earth observation data but regularization strategies are needed to mitigate the drawback of ill-posedness. We systematically evaluated various regularization options to improve leaf chlorophyll content (LCC) and leaf area index (LAI) retrievals over agricultural lands, including the role of (1) cost functions (CFs); (2) added noise; and (3) multiple solutions in LUT-based inversion. Three families of CFs were compared: information measures, M-estimates and minimum contrast methods. We have only selected CFs without additional parame…

PROSAILradiative transfer modelsScienceQEstimatorInversion (meteorology)biophysical parametersLUT-based inversionDatabase normalizationAtmospheric radiative transfer codescost functionsApproximation errorLookup tableGeneral Earth and Planetary Sciencesbiophysical parameters; LUT-based inversion; cost functions; radiative transfer models; PROSAIL; Sentinel-2Sentinel-2Leaf area indexQAImage resolutionRemote sensingMathematicsRemote Sensing; Volume 5; Issue 7; Pages: 3280-3304
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The conditional censored graphical lasso estimator

2020

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. In many applied fields, such as genomics, different types of data are collected on the same system, and it is not uncommon that some of these datasets are subject to censoring as a result of the measurement technologies used, such as data generated by polymerase chain reactions and flow cytometer. When the overall objective is that of network inference, at possibly different levels of a system, information coming from different sources and/or different steps of the analysis can be integrated into one model with the use of conditional graphical models. In this paper, we develop a doubly penalized inferential procedure for…

Statistics and ProbabilityFOS: Computer and information sciencesComputer scienceGaussianInferenceData typeTheoretical Computer Sciencehigh-dimensional settingDatabase normalizationMethodology (stat.ME)symbols.namesakeLasso (statistics)Graphical modelConditional Gaussian graphical modelcensored graphical lassoStatistics - MethodologyHigh-dimensional settingconditional Gaussian graphical modelssparsityEstimatorCensoring (statistics)Censored graphical lassoComputational Theory and MathematicssymbolsCensored dataStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaSparsityAlgorithm
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