We describe an enhanced method for the selection of optimal sensor actions in a probabilistic state estimation framework. We apply this to the selection of optimal focal lengths f...
Benjamin Deutsch, Heinrich Niemann, Joachim Denzle...
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
This paper presents a RTR FPGA embedded in a System on Chip fabricated in 130nm CMOS process. Various aspects of the design flow, from automation to floor-planning are discussed. ...
In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to cre...
Anders Brun, Hans Knutsson, Hae-Jeong Park, Martha...
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...