Cargando…
Variational Beta Process Hidden Markov Models with Shared Hidden States for Trajectory Recognition
Hidden Markov model (HMM) is a vital model for trajectory recognition. As the number of hidden states in HMM is important and hard to be determined, many nonparametric methods like hierarchical Dirichlet process HMMs and Beta process HMMs (BP-HMMs) have been proposed to determine it automatically. A...
Autores principales: | Zhao, Jing, Zhang, Yi, Sun, Shiliang, Dai, Haiwei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534515/ https://www.ncbi.nlm.nih.gov/pubmed/34682013 http://dx.doi.org/10.3390/e23101290 |
Ejemplares similares
-
Recognition of beta-structural motifs using hidden Markov models trained with simulated evolution
por: Kumar, Anoop, et al.
Publicado: (2010) -
Hidden Markov processes: theory and applications to biology
por: Vidyasagar, M
Publicado: (2014) -
Hidden Semi-Markov Models-Based Visual Perceptual State Recognition for Pilots
por: Gao, Lina, et al.
Publicado: (2023) -
Inference in Hidden Markov Models
por: Cappe, Olivier
Publicado: (2005) -
Hidden Markov Modeling with HMMTeacher
por: Fuentes-Beals, Camilo, et al.
Publicado: (2022)