A platform for crowdsourcing the creation of representative, accurate landcover maps
作者： L.D. Estes , D. McRitchie , J. Choi , S. Debats , T. Evans
DOI: 10.1016/J.ENVSOFT.2016.01.011
关键词: Machine learning 、 Representativeness heuristic 、 Artificial intelligence 、 Pattern recognition (psychology) 、 Representative sampling 、 Cover (telecommunications) 、 Geometric data analysis 、 Job market 、 Quality (business) 、 Computer science 、 Crowdsourcing
摘要: … Crowdsourcing map creation may substantially improve accuracy, particularly for discrete cover types, but the quality and representativeness of crowdsourced data is hard to verify. We …
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