Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
In this paper, we propose a new approach for VLSI interconnect global routing that can optimize both congestion and delay, which are often competing objectives. Our approach provi...
This paper presents a global approach for constructing high dynamic range mosaic from multiple images with large exposure differences. By relating image intensities to scene radian...
— Since the original work of Grossglauser and Tse, which showed that the mobility can increase the capacity of an ad hoc network, there has been a lot of interest in characterizi...
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...