Results 41 to 50 of about 24,804 (235)

Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

BMC Bioinformatics, 2006
Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about ...
Borodovsky Mark, Altunbasak Yucel, Aydin Zafer   +2 more
doaj   +1 more source

Performance of hidden Markov model and dynamic Bayesian network classifiers on handwritten Arabic word recognition [PDF]

, 2011
This paper presents a comparative study of two machine learning techniques for recognizing handwritten Arabic words, where hidden Markov models (HMMs) and dynamic Bayesian networks (DBNs) were evaluated.
Jinchang Ren, Alkhateeb, Jawad H., Jiang, J, Ren, J, Pauplin, Olivier, Alkhateeb, JH, Ren, Jinchang, Jawad H. AlKhateeb, Olivier Pauplin, Pauplin, O, Jiang, Jianmin, Jianmin Jiang   +11 more
core   +1 more source

On Regime Switching Models

Mathematics
Regime switching models have been widely studied for their ability to capture the dynamic behavior of time series data and are widely used in economic and financial data analysis.
Zhenni Tan, Yuehua Wu
doaj   +1 more source

Log-Viterbi algorithm applied on second-order hidden Markov model for human activity recognition

International Journal of Distributed Sensor Networks, 2018
Recognition of human activities is getting into the limelight among researchers in the field of pervasive computing, ambient intelligence, robotic, and monitoring such as assistive living, elderly care, and health care.
Yang Sung-Hyun, Keshav Thapa, M Humayun Kabir, Lee Hee-Chan   +3 more
doaj   +1 more source

SMCis: An Effective Algorithm for Discovery of Cis-Regulatory Modules. [PDF]

PLoS ONE, 2016
The discovery of cis-regulatory modules (CRMs) is a challenging problem in computational biology. Limited by the difficulty of using an HMM to model dependent features in transcriptional regulatory sequences (TRSs), the probabilistic modeling methods ...
Haitao Guo, Hongwei Huo, Qiang Yu
doaj   +1 more source

Spatio-temporal categorization for first-person-view videos using a convolutional variational autoencoder and Gaussian processes

Frontiers in Robotics and AI, 2022
In this study, HcVGH, a method that learns spatio-temporal categories by segmenting first-person-view (FPV) videos captured by mobile robots, is proposed.
Masatoshi Nagano, Tomoaki Nakamura, Takayuki Nagai, Takayuki Nagai, Daichi Mochihashi, Ichiro Kobayashi   +5 more
doaj   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Proper account of auto-correlations improves decoding performances of state-space (semi) Markov models

Peer Community Journal
State-space models are widely used in ecology to infer hidden behaviors. This study develops an extensive numerical simulation-estimation experiment to evaluate the state decoding accuracy of four simple state-space models.
Bez, Nicolas, Gloaguen, Pierre, Etienne, Marie-Pierre, Lanco, Sophie, Joo, Rocío, Rivot, Etienne, Walker, Emily, Woillez, Mathieu, Mahévas, Stéphanie   +8 more
doaj   +1 more source

Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces

Advanced Science, EarlyView.
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo, Jinhong Min, Geumbee Lee, Joohoon Kang, Hyoyoung Jeong, Jae‐Young Yoo, Sang Min Won   +9 more
wiley   +1 more source

Global discriminative learning for higher-accuracy computational gene prediction. [PDF]

PLoS Computational Biology, 2007
Most ab initio gene predictors use a probabilistic sequence model, typically a hidden Markov model, to combine separately trained models of genomic signals and content.
Axel Bernal, Koby Crammer, Artemis Hatzigeorgiou, Fernando Pereira   +3 more
doaj   +1 more source