Results 31 to 40 of about 62,966 (184)

What Actually Works for Activity Recognition in Scenarios with Significant Domain Shift: Lessons Learned from the 2019 and 2020 Sussex-Huawei Challenges

Sensors, 2022
From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight different modes of locomotion and transportation using sensor data from ...
Stefan Kalabakov, Simon Stankoski, Ivana Kiprijanovska, Andrejaana Andova, Nina Reščič, Vito Janko, Martin Gjoreski, Matjaž Gams, Mitja Luštrek   +8 more
doaj   +1 more source

Multi-branch Hidden semi-Markov modeling for RUL prognosis [PDF]

2015 Annual Reliability and Maintainability Symposium (RAMS), 2015
Deterioration modeling and remaining useful life (RUL) estimation of equipment are key enabling tasks for the implementation of a predictive maintenance (PM) policy, which plays nowadays an important role for maintaining engineering systems. Hidden Markov Models (HMM) have been used as an efficient tool for modeling the deterioration mechanisms as well
Le, Thanh Trung, Bérenguer, Christophe, Chatelain, Florent   +2 more
openaire   +1 more source

A Sensor-Based Scheme for Activity Recognition in Smart Homes using Dempster-Shafer Theory of Evidence [PDF]

Journal of Artificial Intelligence and Data Mining, 2017
This paper proposes a scheme for activity recognition in sensor based smart homes using Dempster-Shafer theory of evidence. In this work, opinion owners and their belief masses are constructed from sensors and employed in a single-layered inference ...
V. Ghasemi, A. Pouyan, M. Sharifi
doaj   +1 more source

Partially-Hidden Markov Models. [PDF]

, 2012
International audienceThis paper addresses the problem of Hidden Markov Models (HMM) training and inference when the training data are composed of feature vectors plus uncertain and imprecise labels.
Denoeux, Thierry, Ramasso, Emmanuel, Zerhouni, Noureddine   +2 more
core   +7 more sources

Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM [PDF]

Journal of Artificial Intelligence and Data Mining, 2019
Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems ...
M. Asadolahzade Kermanshahi, M. M. Homayounpour   +1 more
doaj   +1 more source

MCMC implementation for Bayesian hidden semi-Markov models with illustrative applications [PDF]

, 2014
Copyright © Springer 2013. The final publication is available at Springer via http://dx.doi.org/10.1007/s11222-013-9399-zHidden Markov models (HMMs) are flexible, well established models useful in a diverse range of applications.
A. Gelman, A. Gelman, A.K. Jardine, C. Jouyaux, C. Yau, C.P. Robert, C.P. Robert, D. Gamerman, D.J. Spiegelhalter, E. Bellone, G. Celeux, H. Kozumi, J. Bulla, J. Bulla, J. Sansom, J.-M. Marin, J.D. Ferguson, J.P. Hughes, L. Rabiner, L.E. Baum, M. Dewar, M. Dong, M. Stephens, P. Fearnhead, P.A. Devijver, R Development Core Team, S. Chib, S. Guha, S. Richardson, S. Scott, S. Scott, S. Tokdar, S.-Z. Yu, S.C. Schmidler, S.E. Levinson, T. Economou, T. Economou, T. Rydén, Theodoros Economou, Trevor C. Bailey, W.R. Gilks, Y. Guedon, Y. Guedon, Y. Kleiner, Zoran Kapelan   +44 more
core   +1 more source

Labeling Self-Tracked Menstrual Health Records With Hidden Semi-Markov Models [PDF]

IEEE Journal of Biomedical and Health Informatics, 2021
AbstractGlobally, millions of women track their menstrual cycle and fertility via smartphone-based health apps, generating multivariate time series with frequent missing data. To leverage data from self-tracking tools in epidemiological studies on fertility or the menstrual cycle’s effects on diseases and symptoms, it is critical to have methods for ...
Laura Symul, Susan Holmes
openaire   +3 more sources

Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals

Complexity, 2018
We present a novel computational technique intended for the robust and adaptable control of a multifunctional prosthetic hand using multichannel surface electromyography.
Nebojša Malešević, Dimitrije Marković, Gunter Kanitz, Marco Controzzi, Christian Cipriani, Christian Antfolk   +5 more
doaj   +1 more source

Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM [PDF]

, 2013
We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known.
Almeida, Babacan, Besag, Bishop, Chao, Chenegros, Daubechies, Degen, Dobigeon, Figueiredo, Forbes, Forbes, Ge, Gilks, Kundur, Landweber, Makni, Makni, Mittelman, Nasios, Orieux, Park, Pillonetto, Robert, Rugar, Shan, Sidles, Sidles, Sidles, Themelis, Ting, Tzikas, Vincent, Walker, Wang, Ward, Winn, Züger, Züger, Züger   +39 more
core   +5 more sources

Graphical models for social behavior modeling in face-to face interaction [PDF]

, 2016
International audienceThe goal of this paper is to model the coverbal behavior of a subject involved in face-to-face social interactions. For this end, we present a multimodal behavioral model based on a Dynamic Bayesian Network (DBN).
Bailly, Gérard, Elisei, Frédéric, Mihoub, Alaeddine, Wolf, Christian   +3 more
core   +2 more sources