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Deep Learning the City: Quantifying Urban Perception at a Global Scale · Study

WorkDeep Learning the City: Quantifying Urban Perception at a Global Scale

Abhimanyu Dubey2016

Work2016

Deep Learning the City: Quantifying Urban Perception at a Global Scale

Abhimanyu Dubey · Nikhil Naik · Devi Parikh · Ramesh Raskar · César A. Hidalgo

606 citations·0/0 files stored·Lecture notes in computer science

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Urban Design and Spatial Analysis Advanced Neural Network Applications Mobile Crowdsensing and Crowdsourcing

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References

2012Great American City 1982BROKEN WINDOWS: THE POLICE AND NEIGHBOURHOOD SAFETY 2012Great American city: Chicago and the enduring neighborhood effect 1997Fixing broken windows: restoring order and reducing crime in our communities 2008The Spreading of Disorder 2013The Collaborative Image of The City: Mapping the Inequality of Urban Perception 2014Divergent Pathways of Gentrification 2003Neighborhood Physical Conditions and Health

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2019A human-machine adversarial scoring framework for urban perception assessment using street-view images 2020A review of urban physical environment sensing using street view imagery in public health studies

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Details

Year2016

Typeother

Published2016-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations606

Files0 public / 0

ShelfUrban Design and Spatial Analysis

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doi10.1007/978-3-319-46448-0_12

openalex_workW2478090196

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