DataScience@UB designs and prototype a machine that includes an intelligent vision system based on semantic segmentation through convolutional neural networks to automate the classification of skins and leather.
Causal data science - Business use case
Artificial intelligence, machine learning and data are at the heart of the digital revolution that citizens, businesses and administrations are experiencing in recent times. These technologies make it possible to identify patterns in the large volume of data they store, and to generate predictions to customize services and products or to automate processes – but lately they have begun to show some shortcomings in supporting decision-making. This is where causal inference and causal data science come in: they allow you to identify the factors that most directly help influence customers’ decisions and quantify their effect.
We have won a new competition with the Cartographic and Geological Institute of Catalonia, to apply deep learning techniques in the detection of changes in the network of infrastructures and constructions in the territory with the aim of automating the process of elaboration of the Topographic map of Catalonia.
Joint development with Vall Hebron Hospital of a scalable medical diagnosis solution based on artificial intelligence tools for CorporateHealth International ApS.