Training convolutional neural networks (CNNs) on large sets of high-resolution images is too computationally intense to be performed on commodity CPUs. Such architectures however ...
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
In this paper a system, which is driven through natural language, that allows operators to select and manipulate objects in the environment using an industrial robot is proposed. I...
Chip-multiprocessors offer increased processing power at a low cost. However, in order to use them for real-time systems, tasks have to be scheduled efficiently and predictably. I...
Energy efficiency is one of important issues in the resource contrained wireless sensor network. In this paper, we propose the authentication and key agreement protocol that effic...
Kyusuk Han, Jangseong Kim, Kwangjo Kim, Taeshik Sh...