Tracking urban gentrification, one building at a time

A new deep-mapping computer model can detect visual changes to individual properties, allowing researchers to more-rapidly track gentrification within neighborhoods and cities, according to a study published March 13, 2019 in the open-access journal PLOS ONE by Lazar Ilic, Michael Sawada, and Amaury Zarzelli of the University of Ottawa, Canada.

from News on Artificial Intelligence and Machine Learning https://ift.tt/2Clo4HM
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