[ANGLÈS] Wireless Sensor Networks (WSNs) are used to monitor physical or environmental conditions, and to pass their data through the network to a central location. These networks have applications in diverse areas including ...

English: Energy harvesting is envisaged as an enabling technology to meet the growing energy demands of the 21st century. The current state of the art allows tapping into several physical and naturally existing sources, ...

Atrial fibrillation (AF) is a growing problem in modern societies with an enormous impact in both short term quality of life and long term survival. A recently developed promising approach to cure AF uses radiofrequency ...

Discovery of causal relations from observational data is a key step toward system's understanding. Standard causal discovery methods fit a new model whenever a new causal graph is presented. Recent works propose to take ...

English: cardiovascular diseases account for more than one third of the annual mortal rate in western countries. Although AF does not directly lead to mortality is pointed as one of the possible causes of stroke. Recent ...

Las redes de sensores inalámbricos se han ido usando cada vez más en los últimos años debido a su capacidad de observar el entorno, procesar datos y tomar decisiones. Estas características han ganado importancia en el ...

The task of Video Object Tracking has for a long time received attention within the field of Computer Vision, and many different approaches have tried to tackle its challenges, being the ones based on appearance and motion ...

[ANGLÈS] Wireless energy harvesting sensors networks constitute a new paradigm, where the motes deployed in the field are no longer constrained by the limited battery resource, but are able to recharge themselves through ...

A dynamic subarray allocation for multi-user massive MIMO systems working in very high frequency bands (mmWave and THz) is proposed as a promising technique to unleash the capacity limits in future cellular networks capable ...

Video Object Segmentation is arguably one of the most challenging tasks in computer vision. Training a model in a supervised manner in this task requires a high number of manually labelled data, which is extremely ...