Techniques to reduce power dissipation for embedded systems have recently come into sharp focus in the technology development. Among these techniques, dynamic voltage scaling (DVS)...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Due to process variations in deep sub-micron (DSM) technologies, the effects of timing defects are difficult to capture. This paper presents a novel coverage metric for estimating...
—Automatic understanding of human behavior is an important and challenging objective in several surveillance applications. One of the main problems of this task consists in accur...
Background modeling plays an important role in video surveillance, yet in complex scenes it is still a challenging problem. Among many difficulties, problems caused by illuminatio...