This year, 143 teams, representing more than 50 universities from 28 different countries (view the map) faced a demanding and innovative business challenge during the qualifiers.
When Computer Vision serves renewable energy production
This year, the qualification challenge of the Data Science Game has focused on concerns for the future, at the intersection between ecology and energy issues; the trial looking at optimizing the production of solar energy.
In order to map the solar energy production potential in France, the OpenSolarMap project provides satellite images of roofs of 80,000 buildings. Based on the individual contributions of users, the orientation of about 15,000 roofs has been categorised. Automatic classification of roof orientation is a true challenge for Etalab, the French public agency in charge of open data and use of data in the administration in France which provided the data.
For the contestants of the Data Science Game, the challenge was to develop an algorithm able to recognise the orientation of a roof from a satellite photograph by building on more than 10,000 photograph of roofs which have been categorized thanks to crowdsourcing.
Great success of Deep Learning
The majority of top 40 teams used Deep Learning methods. These machine learning techniques are known to be particularly efficient on Computer Vision issues and in the context of Big Data.
Thanks to these models, the top 20 teams scored very highly, with between 82 and 87% of good predictions. However good the ranking of the top 3 university contestants – , University Pierre and Marie Curie, Ecole Polytechnique and the University of Amsterdam – , the competion is far from over. For the top 20 universities, it will take far more work and energy to succeed in the final round in September.
After 24 days of competition and 831 algorithms submitted by the 143 teams, the 20 finalists are:
|1||University Pierre and Marie Curie||France|
|3||University of Amsterdam||Netherlands|
|4||Moscow Institute of Physics and Technology||Russia|
|5||Univeristy of Mannheim||Germany|
|6||Moscow State University||Russia|
|9||National University of Singapore||Singapore|
|12||University of Tsukuba||Japan|
|16||RWTH Aachen University||Germany|
|20||University of Padova||Italy|
|22||Indian Statistical Institute||India|
*two teams from Ecole Polytechnique and Columbia University actually reached the top 20 but are not among the finalists because, according to the rules, only one team can represent a university.
See you on 10 and 11 September, 2016!
On 10-11 September, the finalists are invited in Paris for the final stage of this international student hackathon. During the final, the 20 best teams will defend their university and country colors in a Big Data analysis challenge.
For the final phase, the students will be welcomed in the Château Les Fontaines, the training / development campus of of the Capgemini Group. During the competition, the contestants will be able to rely on the expertise and the knowledge of data scientists from Axa and its Data Innovation Lab, Capgemini, Microsoft and Milliman.
Will the Moscow State University, keep its title of Data Science Champion? See you during the final to find out!
Contact: Audrey Ribeiro