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!
Estimate the aesthetic quality of images in order to predict their impact
Image search engines receive huge volumes of images every day, but very few of these have any impact on the internet. Of course, the aesthetics and technique of images are key to ensuring they have an impact on the internet and are not overlooked. The challenge of this project is therefore to develop tools for analysing and predicting the technical and aesthetic quality of images.
An international company and GCD@UB are working on the design of a system to estimate the technical and aesthetic quality of images. This project is being carried out using deep learning networks and large volumes of data with tags related to aesthetics.
Advertising and marketing companies, as well as individual users, are constantly seeking the best images for their projects. Automatically estimating the quality of an image and predicting its impact can help us make decisions about marketing and the economic value of images.
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.