The project proposes an in-depth exploration of advanced machine learning techniques for the automated classification of stellar spectra, aiming to significantly reduce computation time compared to current methods used by Astro+. Beyond improving efficiency, the project envisions the development of models capable of directly determining stellar parameters through deep learning, eliminating the need for manual model fitting. This approach would represent a major step toward fully automated and more efficient spectroscopic analysis.

The project aims to identify the key factors influencing the perception of urban safety in selected neighborhoods of Alicante by analyzing elements such as lighting quality, graffiti, population density, and other relevant indicators. Through the use of artificial intelligence and video analysis tools, it seeks to create an objective, data-driven diagnostic that maps urban conditions affecting perceived safety.

It is intended to develop a set of tools, capable of running on the Unitree Go2 robot, that include mapping, autonomous navigation, and object and person recognition. The developed software will feature a simple interface so that non-expert personnel can use it.

The project aims to create a digital twin that models the cognitive state of older adults to improve their well-being through applications for early detection, monitoring, and personalized assistance against cognitive decline.

Este proyecto busca visibilizar este hecho histórico mediante una aplicación de realidad virtual (RV) que recree los acontecimientos de La Gran Redada relacionados con los castillos de Santa Bárbara y Denia. Este enfoque innovador combina educación, tecnología y promoción del patrimonio...