Results 61 to 70 of about 14,908,682 (295)

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

Modelling human control behaviour with a Markov-chain switched bank of control laws [PDF]

, 1998
A probabilistic model of human control behaviour is described. It assumes that human behaviour can be represented by switching among a number of relatively simple behaviours.
Murray-Smith, R.
core   +4 more sources

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

Prediction Using Markov Model and Hidden Markov Model for the States of Banknotes [PDF]

Alfarama Journal of Basic & Applied Sciences
This study aims to solve the problem of identifying the values of banknotes, and whether if they are fake or not. This problem considered one of the topics that many researchers are interested in the field of detecting banknotes values and determining ...
Mosaad Hendam, Khaled Mahfouz, Mohamed Genedi   +2 more
doaj   +1 more source

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

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

Hidden Markov model hyperparameters.

, 2023
Hidden Markov model hyperparameters.
Connor Brennan (14341166), David Sussillo (162367), Rui Pei (12105620), Adeeti Aggarwal (5130845), Alex Proekt (269515)   +4 more
core   +1 more source

Intrusion detection method based on hierarchical hidden Markov model and variable-length semantic pattern

Tongxin xuebao, 2010
The defects of intrusion detection using fixed-length short system call sequences were analyzed. A method of extracting variable-length short system call sequences, grounded on the function return addresses stored in the process stacks, was proposed ...
DUAN Xue-tao1, JIA Chun-fu 1, LIU Chun-bo1   +2 more
doaj   +2 more sources

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   +3 more sources

Global Stock Selection with Hidden Markov Model

Risks, 2020
Hidden Markov model (HMM) is a powerful machine-learning method for data regime detection, especially time series data. In this paper, we establish a multi-step procedure for using HMM to select stocks from the global stock market.
Nguyet Nguyen, Dung Nguyen
doaj   +1 more source