This paper suggests a decision support system for tactical air combat environment where not much prior information is available about the decision regions. We proposed a combinati...
Computation without stable states is a computing paradigm different from Turing's and has been demonstrated for various types of simulated neural networks. This publication t...
In this paper, we present a neural networks and image analysis based approach to assessing colour deviations in an offset printing process from direct measurements on halftone mult...
A control of real processes requires different approach to neural network learning. The presented modification of backpropagation learning algorithm changes a meaning of learning...
In this thesis we compare several machine learning techniques for evaluating external skeletal fixation proposals. We experimented in the context of dog bone fractures but the pot...
Ning Suo, Khaled Rasheed, Walter D. Potter, Dennis...
We present a neural-network-based statistical parser, trained and tested on the Penn Treebank. The neural network is used to estimate the parameters of a generative model of left-...
Computer security, and intrusion detection in particular, has become increasingly important in today's business environment, to help ensure safe and trusted commerce between ...
This paper deals with the application of a well-known neural network technique, multi-layer back-propagation (BP) neural network, in financial data mining. A modified neural networ...
: Recently, multi-instance classification algorithm BP-MIP and multi-instance regression algorithm BP-MIR both based on neural networks have been proposed. In this paper, neural ne...
In this paper we investigate techniques to train an agent to accomplish certain tasks. Artificial Neural Networks will be the technique used to the train the agent. This paper will...