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...
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...
In this paper we present an algorithm for structure and motion (SM) recovery under affine projection from video sequences. The algorithm tracks the motion of a single structure, b...
—Network delay is a crucial metric for evaluating the state of the network. We present in this paper a structural analysis of network delay, based on delay measurements of a back...
In this paper, we present a graphical model for protein secondary structure prediction. This model extends segmental semi-Markov models (SSMM) to exploit multiple sequence alignme...