Randomized kernels for large scale Earth observation applications

Remote Sensing of Environment

Volumn 202, Issue , 2017, Pages 54-63

  Pérez Suay, Adrián ^a   Amorós López, Julia ^a   Gómez Chova, Luis ^a   Laparra, Valero ^a   Muñoz Marí, Jordi ^a   Camps Valls, Gustau ^a  

^a UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Biophysical parameter estimation; Cloud screening; Copernicus Sentinel 2; Emulation; IASI MetOp; Image classification; Kernel machines; Machine learning; Model inversion; Random features; SEVIRI MSG

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); IMAGE CLASSIFICATION; IMAGE PROCESSING; LEARNING ALGORITHMS; LEARNING SYSTEMS; MAPPING; OBSERVATORIES; RADIATIVE TRANSFER; REMOTE SENSING; SPACE OPTICS;

BIOPHYSICAL PARAMETERS; CLOUD SCREENING; COPERNICUS SENTINEL-2; EMULATION; IASI/METOP; KERNEL MACHINE; MODEL INVERSION; RANDOM FEATURES; SEVIRI/MSG;

PARAMETER ESTIMATION;

ALGORITHM; EOS; IMAGE CLASSIFICATION; MACHINE LEARNING; NUMERICAL MODEL; OBSERVATIONAL METHOD; PARAMETER ESTIMATION; REMOTE SENSING; SENTINEL; TIME SERIES; WAVELENGTH;

EID: 85015678699     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.02.009     Document Type: Article

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