In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the de...
Olivier Y. de Vel, Nianjun Liu, Terry Caelli, Tib&...
The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition. In this work, we pro...
The use of HMM (Hidden Markov Models) for speech recognition has been successful for various applications in the past decades. However, the use of continuous HMM (CHMM) for melody...
Background: Single nucleotide polymorphisms (SNPs) are the most common genetic variations in the human genome and are useful as genomic markers. Oligonucleotide SNP microarrays ha...
Cheng Li, Rameen Beroukhim, Barbara A. Weir, Wendy...
A method for automatically assessing the constructional sequence from a neuropsychological drawing task using Hidden Markov Models is presented. We also present a method of extrac...
Richard M. Guest, Samuel Chindaro, Michael C. Fair...