A new way to automatically build road maps from aerial images
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“RoadTracer” system from MIT’s Computer Science and Artificial Intelligence Laboratory could reduce workload for developers of apps like Google Maps.
Source: mit.edu

“RoadTracer” system from MIT’s Computer Science and Artificial Intelligence Laboratory could reduce workload for developers of apps like Google Maps.
Source: mit.edu
The pico.js library is a JavaScript implementation of the method described in 2013 by Markuš et al. in a technical report. The reference implementation is written in C and available on GitHub: https://github.com/nenadmarkus/pico.
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As detailed in a paper published to arXiv, the neural net is actually a generative adversarial network (GAN), which is a way of training a machine learning algorithm without human supervision. In GANs, two neural nets are pitted against one another: One neural net generates new images and tries to trick the other neural net into thinking the images are real. If the other neural net is able to tell the generated images are false
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Location and navigation using global positioning systems (GPS) is deeply embedded in our daily lives, and is particularly crucial to Uber’s services. To orchestrate quick, efficient pickups, our GPS technologies need to know the locations of matched riders and drivers, as well as provide navigation guidance from a driver’s current location to where the rider needs to be picked up, and then, to the rider’s chosen destination. For this process to work seamlessly, the location estimates for riders and drivers need to be as precise as possible.
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