Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn Part F129685, Issue , 2017, Pages 1357-1366

  Albert, Adrian ^a   Kaur, Jasleen ^b   Gonzalez, Marta C ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b Philips Design North America   (United States)

Author keywords

Convolutional networks; Land use classification; Satellite imagery

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; CONVOLUTION; DATA MINING; DEEP NEURAL NETWORKS; DEVELOPING COUNTRIES; ECONOMICS; IMAGE CLASSIFICATION; IMAGE SEGMENTATION; INVESTMENTS; LAND USE; LEARNING SYSTEMS; NEURAL NETWORKS; REMOTE SENSING; SATELLITES; URBAN PLANNING;

COMPUTER VISION TECHNIQUES; CONVOLUTIONAL NETWORKS; CONVOLUTIONAL NEURAL NETWORK; LANDUSE CLASSIFICATIONS; LARGE-SCALE SATELLITES; PLANNING APPLICATIONS; REMOTE SENSING APPLICATIONS; REMOTE SENSING DATA;

SATELLITE IMAGERY;

EID: 85029032529     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/3097983.3098070     Document Type: Conference Paper

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