VPRS-Based regional decision fusion of CNN and MRF classifications for very fine resolution remotely sensed images

IEEE Transactions on Geoscience and Remote Sensing

Volumn 56, Issue 8, 2018, Pages 4507-4521

  Zhang, Ce ^a   Sargent, Isabel ^b   Pan, Xin ^c,d   Gardiner, Andy ^b   Hare, Jonathon ^e   Atkinson, Peter M ^a  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b ORDNANCE SURVEY   (United Kingdom)

^c CHANGCHUN INSTITUTE OF TECHNOLOGY   (China)

^d NORTHEAST INSTITUTE OF GEOGRAPHY AND AGRICULTURAL ECOLOGY   (China)

^e UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Convolutional neural network (CNN); Markov random field (MRF); regional fusion decision; rough set; uncertainty

Indexed keywords

CONVOLUTION; DEEP NEURAL NETWORKS; IMAGE FUSION; IMAGE SEGMENTATION; MARKOV PROCESSES; NEURAL NETWORKS; ROUGH SET THEORY; SEMANTICS; STRUCTURAL FRAMES;

COMPLEMENTARY CHARACTERISTICS; CONVOLUTIONAL NEURAL NETWORK; CONVOLUTIONAL NEURAL NETWORKS (CNN); MARKOV RANDOM FIELDS; REGIONAL FUSION DECISION; UNCERTAINTY; UNCERTAINTY DISTRIBUTIONS; VARIABLE PRECISION ROUGH SETS;

IMAGE CLASSIFICATION;

ARTIFICIAL NEURAL NETWORK; COMPUTER VISION; DATA SET; IMAGE CLASSIFICATION; IMAGE RESOLUTION; MODEL; NUMERICAL METHOD; PATTERN RECOGNITION; REMOTE SENSING; SATELLITE IMAGERY; SPATIAL RESOLUTION; SUPPORT VECTOR MACHINE; UNCERTAINTY ANALYSIS;

ENGLAND; UNITED KINGDOM;

EID: 85045743328     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2018.2822783     Document Type: Article

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