This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
We present a formal description of a neurofuzzy system capable of aligning two sequences recognizing their internal structure. The alignment is done on two levels: grouping of the...
The purpose of this article is to define optic flow for scalar and density images without using a priori knowledge other than its defining conservation principle, and to incorpo...
Abstract. This paper describes the setup of the Book Structure Extraction competition run at ICDAR 2009. The goal of the competition was to evaluate and compare automatic technique...
Antoine Doucet, Gabriella Kazai, Bodin Dresevic, A...