cat.
01.01.1970
Artificial intelligence, machine learning and data are at the heart of the digital revolution we are currently experiencing. To support business decision-making, one must go beyond predictions and employ causal data science, which enables you to identify the factors that most directly help influence customer decision-making. We explain it in this video!
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.
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.
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 leather.
Thanks to the emerging technologies of e-Learning, the analysis of data offers professionals in the education sector, advantages with the ability to impact and revolutionize in the future the way we analyze and evaluate the learning experience.
Within the framework of the Cartographic Plan of Catalonia, the Cartographic and Geological Institute of Catalonia is working on the elaboration of the technical specifications of the land covers Map of Catalonia. The ICGC has commissioned us a study to explore the viability of the application of deep learning techniques in the generation of maps.
A company in the online sector has generated a large volume of data that provides a history to be able to extract information from clients and develop a predictive model based on the behavior of users. This behavior include the navigation through the platform, the interaction with others channels, messages to the community, etc. The ultimate goal is to provide a better customer service by recommending products based on the specific time of the customer journey.