A Platform for Spatial Data Labeling in an Urban Context
2012
This chapter presents a platform for classifying urban areas, improved by a machine learning framework able to ease this classification. We propose thanks to this platform an iterative procedure for geographic experts that have to define classes or “labels” and then classify in a semi-automated way. This work is part of the GeOpenSim project and has been developed within the Geoxygene framework.
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