Results 41 to 50 of about 8,467,026 (293)

A coupled hidden Markov model for disease interactions [PDF]

, 2012
To investigate interactions between parasite species in a host, a population of field voles was studied longitudinally, with presence or absence of six different parasites measured repeatedly.
Telfer, S.E., Xifara, Tatiana, Begon, M., Chris Sherlock, Mike Begon, Ra Telfer, Sherlock, Chris, Tatiana Xifara, Begon, Mike, Sherlock, Christopher, Telfer, Sandra, Sandra Telfer   +11 more
core   +1 more source

Robotic Assistants in the Operating Room: A Systematic Review of Vision‐Based Systems for Nonoperative Tasks

Advanced Robotics Research, EarlyView.
This review brings together 20 publications describing 11 robotic system families developed for instrument handling, sterile‐package opening, supply delivery, and operating room logistics. Perception is becoming more capable through deep learning and language‐guided control, but autonomy remains limited, evidence is largely laboratory‐based, and no ...
Eugenia Mawuenya Akpo, Pietro Falco, Nicholas Raison, Christos Bergeles, Letizia Gionfrida   +4 more
wiley   +1 more source

Time series segmentation with shifting means hidden markov models [PDF]

Nonlinear Processes in Geophysics, 2006
We present a new family of hidden Markov models and apply these to the segmentation of hydrological and environmental time series. The proposed hidden Markov models have a discrete state space and their structure is inspired from the shifting means ...
Ath. Kehagias, V. Fortin
doaj  

SemanticST: A Scalable Multi‐Contextual Graph Learning Framework for Uncovering Spatial Niches and Robust Multi‐Sample Integration in Spatial Transcriptomics

Advanced Science, EarlyView.
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi, Ahmadreza Argha, Nona Farbehi, Ivan Bakhshayeshi, Thantrira Porntaveetus, Youqiong Ye, Nigel H. Lovell, Hamid Alinejad‐Rokny   +7 more
wiley   +1 more source

Hidden Markov Models

Applied Medical Informatics, 2011
Hidden Markov models (HMMs) are a highly effective means of modeling a family of unaligned sequences or a common motif within a set of unaligned sequences. The trained HMM can then be used for discrimination or multiple alignment.
Mihaela IANCU
doaj  

Deep‐Learning‐Based Denoising for Improved Phase Precision in Electron Holography of Electromagnetic Fields in Nanoscale Materials

Advanced Science, EarlyView.
Low‐dose electron holography is limited by shot noise, which buries weak phase signals. HoloDenoiser, a physics‐informed network that works simultaneously in the spatial and frequency domains, locates and protects the holographic sideband while suppressing noise in the hologram.
Ye Luo, Luyang Wang, Zhiling Yu, Xiaowen Chen, Xiaoyu Wang, Ya‐Hui Jia, Thibaud Denneulin, Yu Han, Rafal E. Dunin‐Borkowski, Fengshan Zheng, Qi Liu   +10 more
wiley   +1 more source

Semi-Markov and hidden semi-Markov models of energy systems

E3S Web of Conferences, 2018
The problem of information control systems creation for energy systems and transition to intelligent control and engineering is one of the important problems of reliability and efficiency theory for energy systems.
Obzherin Yuriy E.
doaj   +1 more source

Using Hidden Markov Chains in Recognition of Vowel Letters in English Language [PDF]

المجلة العراقية للعلوم الاحصائية, 2006
This study deals with hidden Markov models . These models consist of sets of finite states , each one of them is associated with a probability distribution .
doaj   +1 more source

A statistical multiresolution approach for face recognition using structural hidden Markov models [PDF]

, 2007
This paper introduces a novel methodology that combines the multiresolution feature of the discrete wavelet transform (DWT) with the local interactions of the facial structures expressed through the structural hidden Markov model (SHMM).
A. Amira, P Nicholl, D. Bouchaffra, Perrott, R H, P. Nicholl, R H Perrott, Perrott, RH, D Bouchaffra, Nicholl, P, Amira, A, Bouchaffra, D, A Amira, R. H. Perrott   +12 more
core   +1 more source

An ATP‐Driven N Protein–DDX21 Molecular Switch Dynamically Controls SARS‐CoV‐2 RNA G‐Quadruplex Heterogeneity

Advanced Science, EarlyView.
An ATP‐driven molecular switch, comprising viral nucleocapsid (N) protein and host helicase DDX21, dynamically modulates SARS‐CoV‐2 RNA G‐quadruplex (G4) heterogeneity. These viral G4s feature non‐canonical ion‐dependence and act as energy‐sensitive structural checkpoints.
Ya‐Ting Zheng, Li‐Yan Zhai, Jie Jin, Qiu‐Ying Chen, Hang Fu, Xue‐Qian Sun, Ying Lu, Hui Li, Xi‐Miao Hou   +8 more
wiley   +1 more source