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.
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.
Invalcor is a center specialized in the functional assessment of the locomotor system that by means of advanced technology objective aspects such as the measure of the mobility, strength, power, resistance, or fatigue of a damaged body region. The company is interested in designing a prediction system that, based on the historical data of its activity, attends the diagnosis work to doctors.
This project consisted of the development of a tool for learning about the different relationships between the members of an organisation and their areas of work. The group-level analysis provides a real-time diagnosis and makes it possible to take actions to improve and streamline processes.