Large Astronomical Surveys
Identify rare galaxy/galaxy collisions in Big Data from astronomical imaging data.
Astronomers are capturing terabytes of imaging data of distant galaxies. The number of these detected galaxies can range into the billions and beyond. In order to scientifically analyze them, astronomers need to classify them.
Astronomers can use training sets of well studied galaxies, as well as computer simulated images, to develop their own machine learning galaxy classifiers.
Modulos makes it easy for scientists to try out different models and training sets to find an optimal classifier to speed up their research projects.