Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
A system for the automatic segmentation of fluorescence micrographs is presented. In a first step positions of fluorescent cells are detected by a fast learning neural network, whi...
Tim W. Nattkemper, Heiko Wersing, Walter Schubert,...
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
We show how to improve a state-of-the-art neural network language model that converts the previous "context" words into feature vectors and combines these feature vectors...
In this paper, a recurrent neural network is used to develop a dynamic controller for mobile robots. The advantage of the control approach is that no knowledge about the robot mode...
Mohamed Oubbati, Michael Schanz, Thorsten Buchheim...