Deep learning-based classification of hyperspectral data

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

Volumn 7, Issue 6, 2014, Pages 2094-2107

  Chen, Yushi ^a   Lin, Zhouhan ^a   Zhao, Xing ^a   Wang, Gang ^b   Gu, Yanfeng ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Autoencoder (AE); deep learning; feature extraction; hyperspectral data classification; logistic regression; stacked autoencoder (SAE); support vector machine (SVM)

Indexed keywords

FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

AUTO ENCODERS; CLASSIFICATION ACCURACY; COMPETITIVE PERFORMANCE; DEEP LEARNING; HYPERSPECTRAL DATA CLASSIFICATION; HYPERSPECTRAL REMOTE SENSING; LOGISTIC REGRESSIONS; PRINCIPLE COMPONENT ANALYSIS;

NETWORK ARCHITECTURE;

ACCURACY ASSESSMENT; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; LOGISTICS; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; REMOTE SENSING; SPECTRAL ANALYSIS;

EID: 84905925092     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2014.2329330     Document Type: Article

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