Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
In this work, we investigate how illuminant estimation techniques can be improved, taking into account automatically extracted information about the content of the images. We consi...
Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential to significantly impro...
We study the problem of designing a survivable WDM network based on covering the communication requests with subnetworks that are protected independently from each other. We consi...
Hardware accelerators are becoming a highly appealing approach to boost the raw performance as well as the price-performance and power-performance ratios of current clusters. In t...
Manuel Fogue, Francisco D. Igual, Enrique S. Quint...