A rough set decision tree based MLP-CNN for very high resolution remotely sensed image classification

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 42, Issue 2W7, 2017, Pages 1451-1454

  Zhang, C ^a   Pan, X ^b   Zhang, S Q ^c   Li, H P ^c   Atkinson, P M ^a  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b CHANGCHUN INSTITUTE OF TECHNOLOGY   (China)

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

Author keywords

Convolutional neural network; Decision tree; Fusion decision; Multilayer perceptron; Rough set theory; VHR remotely sensed imagery

Indexed keywords

DECISION THEORY; DECISION TREES; IMAGE CLASSIFICATION; LEARNING SYSTEMS; MULTILAYER NEURAL NETWORKS; NEURAL NETWORKS; REMOTE SENSING;

CLASSIFICATION METHODS; CLASSIFICATION PERFORMANCE; CLASSIFICATION RESULTS; CONVOLUTIONAL NEURAL NETWORK; MULTI LAYER PERCEPTRON; REMOTELY SENSED IMAGERY; SPECTRAL DIFFERENTIATION; VERY HIGH RESOLUTION (VHR) IMAGE;

ROUGH SET THEORY;

EID: 85030999106     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5194/isprs-archives-XLII-2-W7-1451-2017     Document Type: Conference Paper

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