We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
In this paper, we propose an "in-network" diversity combining scheme for image transport over wireless sensor networks. We consider a wireless sensor network with both w...
IEEE 802.11 and Mote devices are today two of the most interesting wireless technologies for ad hoc and sensor networks respectively, and many efforts are currently devoted to und...
Giuseppe Anastasi, Eleonora Borgia, Marco Conti, E...
Understanding neural connectivity and structures in the brain requires detailed 3D anatomical models, and such an understanding is essential to the study of the nervous system. Ho...
This paper presents a novel method for training hidden Markov models (HMMs) for use in HMM-based speech synthesis. The primary goal of HMM parameter optimization is to ensure that...