Learning source-invariant deep hashing convolutional neural networks for cross-source remote sensing image retrieval

IEEE Transactions on Geoscience and Remote Sensing

Volumn 56, Issue 11, 2018, Pages 6521-6536

  Li, Yansheng ^a   Zhang, Yongjun ^a   Huang, Xin ^a   Ma, Jiayi ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Cross source large scale remote sensing image retrieval (CS LSRSIR); dual source remote sensing image data set (DSRSID); remote sensing big data (RSBD) management and mining; source invariant deep hashing convolutional neural networks (SIDHCNNs)

Indexed keywords

BIG DATA; CONVOLUTION; DATA MINING; DEEP NEURAL NETWORKS; IMAGE RETRIEVAL; NEURAL NETWORKS;

CONVOLUTIONAL NEURAL NETWORK; DUAL SOURCE; END TO END; LAND COVER; LEARNING SOURCES; REMOTE SENSING DATA SOURCE; REMOTE SENSING IMAGE RETRIEVAL; REMOTE SENSING IMAGES;

REMOTE SENSING;

ARTIFICIAL NEURAL NETWORK; DATA SET; IMAGE ANALYSIS; LEARNING; MACHINE LEARNING; OPTIMIZATION; REMOTE SENSING;

UNITED STATES;

EID: 85048536085     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2018.2839705     Document Type: Article

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