This paper describes a Neural Network (NN) approach for logical document structure extraction. In this NN architecture, called Transparent Neural Network (TNN), the document struct...
We propose a neural network based autoassociative memory system for unsupervised learning. This system is intended to be an example of how a general information processing architec...
There is increasing evidence to suggest that the neocortex of the mammalian brain does not consist of a collection of specialised and dedicated cortical architectures, but instead ...
John Thornton, Torbjorn Gustafsson, Michael Blumen...
A novel type of higher order pipelined neural network, the polynomial pipelined neural network, is presented. The network is constructed from a number of higher order neural networ...
Abir Jaafar Hussain, Adam Knowles, Paulo J. G. Lis...
This paper presents a novel approach for detecting network intrusions based on a competitive learning neural network. In the paper, the performance of this approach is compared to...
This paper proposes the use of neural network ensembles to boost the performance of a neural network based surface reconstruction algorithm. Ensemble is a very popular and powerfu...
Ioannis P. Ivrissimtzis, Yunjin Lee, Seungyong Lee...
In this paper the node-level decision unit of a self-learning anomaly detection mechanism for office monitoring with wireless sensor nodes is presented. The node-level decision uni...
The accurate prediction of enzyme catalytic sites remains an open problem in bioinformatics. Recently, several structure-based methods have become popular; however, few robust seq...
We present an application of arti cial neural networks to machine condition monitoring. Since several signal preprocessing methods produce high dimensional feature vectors there i...
The implementation of larger digital neural networks has not been possible due to the real-estate requirements of single neurons. We present an expandable digital architecture whic...
Valentina Salapura, Michael Gschwind, Oliver Maisc...