ICT Journal | Bühler relies on machine learning to separate the wheat grain from the chaff [In French]

The SDSC and Idiap have partnered to develop Renku, a cutting-edge collaborative data science platform.

50 proposals were selected through the review processes of the SDSC's first National Calls.

Press Release: The SDSC has announced its support for 50 proposals, carefully selected through its 1st National Calls.

The goal of CarboSense4D is to produce an accurate map of the evolution of carbon dioxide over Switzerland by applying machine learning methods from a network of low-cost sensors.

Not all datasets are images and we need architectures that adapt to other types of data, encoding both domain specific knowledge and data specific characteristics. For instance, at the SDSC, we deal with spherical data, i.e. curved images on a sphere, but without clear borders and arbitrary orientation.