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Study uses computer vision algorithm to study Google Street View images for signs of urban change. Black Parents White Baby Update more. Download Naruto Shippuden Episode 317 Subtitle Indonesia Mkv here. Credit: CC0 Public Domain. Harvard scientists are among the co- authors of a new study that uses computer vision algorithms to examine millions of Google Street View images to measure whether and how urban areas are changing. The study both found that two key demographic characteristics - high density and high education - play important roles in urban improvement, and showed support for three classical theories of urban change.

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Glaeser, the Fred and Eleanor Glimp Professor of Economics at Harvard and C. Hidalgo and Ramesh Raskar, associate professors at the MIT Media Lab, Kominers, an Associate Professor in the Entrepreneurial Management Unit at HBS and the Department of Economics and Naik, a Prize Fellow in Economics, History and Politics, authored a study that uses computer vision algorithms to examine millions of Google Street View images in an effort to measure whether and how urban areas are changing. In addition to demonstrating the effectiveness of the technology, the study both found that two key demographic characteristics - high density and high education - play important roles in urban improvement, and showed support for three classical theories of urban change. The study is described in a July 6 paper in Proceedings of the National Academy of Sciences. What's more, they keep those maps up- to- date by periodically re- photographing the same locations in major cities. Consequently, Street View contains a rich database of urban images that researchers can use to follow cities through time. Using Street View images to track urban change isn't a new idea, though.

In 2. 01. 4, then- doctoral student Jackelyn Hwang and Robert Sampson, the Henry Ford II Professor of the Social Sciences, published a pioneering study that employed a team of volunteers to analyze Street View images and locate signs of gentrification across 3,0. Chicago. Naik and co- authors took this idea a step further by using artificial intelligence to automate the process. The authors also found evidence for the . And the patterns of urban change we see help illustrate why urban inequality persists. Sloan Foundation, a Star Family Challenge grant, the National Science Foundation, the Harvard Milton Fund, the Ng Fund of the Harvard Center of Mathematical Sciences and Applications, the Human Capital and Economic Opportunity Working Group sponsored by the Institute for New Economic Thinking, the Taubman Center for State and Local Government, the Google Living Labs Award and a gift from Facebook.

Computer vision uncovers predictors of physical urban change, Proceedings of the National Academy of Sciences (2. DOI: 1. 0. 1. 07.