In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...
Abstract - A robust method for symbol recognition is presented that utilizes a compact signature based on a modified Hough Transform (HT) and knowledge-based hierarchical neural ne...
This paper considers a minimum cost flow problem where arc costs are uncertain, and the decision maker wishes to minimize both the expected flow cost and the variance of this co...
— This paper describes an ontology-driven model, which integrates Bayesian Networks (BN) into the Ontology Web Language (OWL) to preserve the advantages of both. This model makes...
Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
Raphael Mourad, Christine Sinoquet, Philippe Leray