Learning multiscale and deep representations for classifying remotely sensed imagery

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 113, Issue , 2016, Pages 155-165

  Zhao, Wenzhi ^a   Du, Shihong ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Deep learning; Feature extraction; Multiscale convolutional neural network (MCNN); Remote sensing image classification

Indexed keywords

CONVOLUTION; DATA MINING; FEATURE EXTRACTION; IMAGE CLASSIFICATION; IMAGE RECONSTRUCTION; NEURAL NETWORKS; REMOTE SENSING;

CLASSIFICATION ACCURACY; CLASSIFICATION RESULTS; CONTEXTUAL INFORMATION; CONVOLUTIONAL NEURAL NETWORK; DEEP LEARNING; REMOTE SENSING IMAGE CLASSIFICATION; REMOTELY SENSED IMAGERY; VERY HIGH RESOLUTION (VHR) IMAGE;

CLASSIFICATION (OF INFORMATION);

ALGORITHM; DATA SET; EXPERIMENTAL STUDY; HIERARCHICAL SYSTEM; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGERY; LEARNING; REMOTE SENSING; URBAN AREA;

EID: 84956620231     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2016.01.004     Document Type: Article

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