Exploring geo-tagged photos for land cover validation with deep learning

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 141, Issue , 2018, Pages 237-251

  Xing, Hanfa ^a,b   Meng, Yuan ^b   Wang, Zixuan ^b   Fan, Kaixuan ^b   Hou, Dongyang ^b  

^a SOUTH CHINA NORMAL UNIVERSITY   (China)

^b SHANDONG NORMAL UNIVERSITY   (China)

Author keywords

Accuracy assessment; Convolutional neural network; Crowdsourced photos; Land cover; Sample classification

Indexed keywords

IMAGE ENHANCEMENT; MAPS; NEURAL NETWORKS; PROBABILITY DISTRIBUTIONS;

ACCURACY ASSESSMENT; CONVOLUTIONAL NEURAL NETWORK; CROWDSOURCED PHOTOS; LAND COVER; SAMPLE CLASSIFICATION;

DEEP LEARNING;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; DATA INTERPRETATION; HETEROGENEITY; LAND COVER; LEARNING; MODEL VALIDATION; PROBABILITY; RECOGNITION; REMOTE SENSING; SATELLITE IMAGERY; TAGGING;

CALIFORNIA; UNITED STATES;

EID: 85046867280     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2018.04.025     Document Type: Article

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