Results 131 to 140 of about 63,611 (263)

Unsupervised Work Behavior Pattern Extraction Based on Hierarchical Probabilistic Model

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
In this study, we address the challenge of analyzing worker behaviors in high‐mix, low‐volume production environments, where traditional supervised learning methods struggle owing to the lack of labeled data and task variability among workers. To overcome these issues, we propose a novel hierarchical approach for unsupervised behavior pattern ...
Issei Saito, Tomoaki Nakamura, Toshiyuki Hatta, Wataru Fujita, Shintaro Watanabe, Shotaro Miwa   +5 more
wiley   +1 more source

The hidden Markov model and its applications in bioinformatics analysis. [PDF]

Genes Dis
Ma Y, Chen H, Kang J, Guo X, Sun C, Xu J, Tao J, Wei S, Dong Y, Tian H, Lv W, Jia Z, Bi S, Shang Z, Zhang C, Lv H, Jiang Y, Zhang M.   +17 more
europepmc   +1 more source

A reaction network scheme for hidden Markov model parameter learning. [PDF]

J R Soc Interface, 2023
Wiuf C, Behera A, Singh A, Gopalkrishnan M.   +3 more
europepmc   +1 more source

Classification of summarized videos using hidden markov models on compressed chromaticity signatures [PDF]

, 2001
Cheng Lu, Mark S. Drew, James Au
openalex   +1 more source

Applications of Artificial Intelligence in Neurological Voice Disorders

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Neurological voice disorders, such as Parkinson's disease, laryngeal dystonia, and stroke‐induced dysarthria, significantly impact speech production and communication. Traditional diagnostic methods rely on subjective assessment, whereas artificial intelligence (AI) offers objective, noninvasive, and scalable solutions for voice analysis. This
Dongren Yao, Aki Koivu, Kristina Simonyan   +2 more
wiley   +1 more source

Noise reduction of low-dose electron holograms using the wavelet hidden Markov model. [PDF]

Microscopy (Oxf)
Tomita Y, Midoh Y, Tamaoka T, Murakami Y.   +3 more
europepmc   +1 more source

Behavioural responses of brown bears to helicopter capture

Wildlife Biology, EarlyView.
Understanding the effects of capture and handling on wild animals is crucial in evaluating ethical practices in ecological research, and in avoiding biased conclusions from misinterpreting biologging data potentially affected by capture. The aim of this study was to assess the effects of helicopter capture on the behaviour of Scandinavian brown bears ...
Alexandra Thiel, Anne G. Hertel, Boris Fuchs, Andrea Friebe, David Ahlqvist, Anne Randi Græsli, Sylvain Giroud, Jonas Kindberg, Jon M. Arnemo, Alina L. Evans   +9 more
wiley   +1 more source

Dynamic reconfiguration and transition of whole-brain networks in patients with MELAS revealed by a hidden Markov model. [PDF]

Front Neurol
Yu Q, Wang R, Sun C, Hu B, Liu X, Yang L, Lin J, Geng D, Li Y.   +8 more
europepmc   +1 more source

Inferring school district learning modalities during the COVID-19 pandemic with a hidden Markov model. [PDF]

PLoS One, 2023
Panaggio MJ, Fang M, Bang H, Armstrong PA, Binder AM, Grass JE, Magid J, Papazian M, Shapiro-Mendoza CK, Parks SE.   +9 more
europepmc   +1 more source

Effective hidden Markov models for detecting splicing junction sites in DNA sequences [PDF]

, 2001
Michael M. Yin, Jason T. L. Wang
openalex   +1 more source