Superpixel-Based Active Learning and Online Feature Importance Learning for Hyperspectral Image Analysis

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 10, Issue 1, 2017, Pages 347-359

  Guo, Jielian ^a   Zhou, Xiong ^a   Li, Jun ^b   Plaza, Antonio ^c   Prasad, Saurabh ^a  

^a UNIVERSITY OF HOUSTON   (United States)

^b SUN YAT SEN UNIVERSITY   (China)

^c UNIVERSITY OF EXTREMADURA   (Spain)

Author keywords

Active learning (AL); hyperspectral; superpixel

Indexed keywords

ALUMINUM; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); HYPERSPECTRAL IMAGING; IMAGE ANALYSIS; IMAGE RECONSTRUCTION; MAPPING; NETWORK FUNCTION VIRTUALIZATION; PIXELS; REMOTE SENSING; SPECTROSCOPY;

ACTIVE LEARNING; CLASSIFICATION TASKS; HYPERSPECTRAL; OPTICAL IMAGING SENSORS; REMOTE SENSING IMAGES; STATE-OF-THE-ART APPROACH; SUPER PIXELS; URBAN LAND COVER CLASSIFICATION;

E-LEARNING;

IMAGE ANALYSIS; IMAGE CLASSIFICATION; MACHINE LEARNING; PIXEL; REMOTE SENSING; SPECTRAL ANALYSIS;

EID: 85019346966     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2016.2609404     Document Type: Article

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