Currency converter
^
All news
News Search Topics
ОК
Use filter
You can filter your feed,
by choosing only interesting
sections.
Loading

Skoltech’s service joins ranks of best geoinformatics technologies

May 30, 14:00 UTC+3 MOSCOW

The service makes it possible to recognize the contours and heights of buildings using ordinary (not stereo) images from satellites

Share
1 pages in this article
© Dmitriy Serebryakov/TASS

MOSCOW, May 30. /TASS/. The CityEye project presented by employees of AeroNet Lab (CDISE) at the Skolkovo Institute of Science and Technology (Skoltech) has taken second place in the hackathon on geoinformatics technologies at Innopolis University. This development was reported by Skoltech’s press office.

The second "Card Reading" hackathon devoted to the development of geoinformatics services for business and the general public was held at Kazan’s Innopolis University on May 19-20. The chief subject of 2018 covered technologies for processing Earth remote sensing data.

The CityEye project presented by employees of Skoltech’s AeroNet Lab (CDISE) took second place in the hackathon on geoinformatics technologies. CityEye, also known as Geoalert City, is an online service based on an AI platform for processing Earth remote sensing data created in the laboratory.

It should be distinctly highlighted that the service makes it possible to recognize the contours and heights of buildings using ordinary (not stereo) images from satellites. In addition, anyone can get an accurate estimate of the population size and the number of objects with precision so sharp it can pinpoint a single house. Data like this is needed for evaluating investments and the viability of putting up new buildings. For example, an incorrectly chosen spot to construct a store may entail serious losses for its owner.

"Communicating with mentors from the industry was very enlightening for us. We got an understanding of the difficulties in creating a commercially attractive final product even when we have a finished and high-demand technical solution," said Pavel Parunin, a project representative.

AeroNet Lab’s laboratories deal with the development of various applications based on methods of deep learning and computer vision to solve practical tasks using data from satellites and aerial photography including services for monitoring restricted areas of extensive industrial objects and services for monitoring forestry and agriculture.

Show more
Share
In other media
ADVERTISEMENT
Partner News
ADVERTISEMENT