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.
Application of deep learning techniques in the detection of changes and generation of maps of land covering of Catalonia (MCSC).
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.
Up to now, land cover maps of the territory have been manually worked on from orthophotographic images. The comparison of the covers between the different temporal periods in which images were taken was done manually as well. The DataScience@UB group is developing a model in order to include image segmentation processes based on deep learning techniques for the automatic construction of maps of the land covers of the territory.
Dispose of updated maps at shorter time intervals favoring a better interpretation of the territory for territorial and urban planning.
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.