Results 61 to 70 of about 6,955,768 (244)
Advances in Mechanical Engineering, 2017 How to improve the accuracy and algorithm efficiency of bearing fault diagnosis has been the focus and hot topic in fault diagnosis field. Deep belief network is a typical deep learning method, which can be used to form a much higher-level abstract ...
Dongying Han, Na Zhao, Peiming Shi
doaj +1 more source
Statistics and Deep Belief Network-Based Cardiovascular Risk Prediction [PDF]
Healthcare Informatics Research, 2017 ObjectivesCardiovascular predictions are related to patients' quality of life and health. Therefore, a risk prediction model for cardiovascular conditions is needed.MethodsIn this paper, we propose a cardiovascular disease prediction model using the ...
Jaekwon Kim, Ungu Kang, Youngho Lee
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From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Hyperspectral Data Feature Extraction Using Deep Belief Network
, 2016 Hyperspectral data has rich spectrum information, strong correlation between bands and high data redundancy. Feature band extraction of hyperspectral data is a prerequisite and an important basis for the subsequent study of classification and target ...
Jiang Xinhua +3 more
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Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Object-based Urban Land Use Classification using Deep Belief Network [PDF]
, 2018 Urban land use information is very important for urban planning, regional administration and management. Classification of urban land use from high resolution images remains a challenging task, due to the extreme difficulties in differentiating complex ...
Su Wai Tun, Khin Mo Mo Tun
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Deep Belief Network and Auto-Encoder for Face Classification
International Journal of Interactive Multimedia and Artificial Intelligence, 2019 The Deep Learning models have drawn ever-increasing research interest owing to their intrinsic capability of overcoming the drawback of traditional algorithm.
Nassih Bouchra +3 more
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Behavior-based driver fatigue detection system with deep belief network
, 2022 Traffic accidents as a result of driver fatigue and drowsiness have caused many injuries and deaths. Therefore, driverfatigue detection and prediction system have been recognized as important potential research areas to prevent accidentscaused by fatigue
Becerikli, Yaşar, Kır Savaş, Burcu
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Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source
Structure‐forward targeting of claudins with synthetic binders
FEBS Letters, EarlyView.Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley +1 more source