AIMC Topic: Bayes Theorem

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Automated system for classification of COVID-19 infection from lung CT images based on machine learning and deep learning techniques.

Scientific reports Oct 18, 2022
The objectives of our proposed study were as follows: First objective is to segment the CT images using a k-means clustering algorithm for extracting the region of interest and to extract textural features using gray level co-occurrence matrix (GLCM)...
Machine Learning COVID-19 Tomography, X-Ray Computed Lung Humans Bayes Theorem Deep Learning
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Bayesian Pseudoinverse Learners: From Uncertainty to Deterministic Learning.

IEEE transactions on cybernetics Oct 17, 2022
Pseudo-inverse learners (PILs) are a kind of feedforward neural network trained with the pseudoinverse learning algorithm, which can be traced back to 1995 originally. PIL is an approach for nongradient descent learning, and its main advantage is the...
Neural Networks, Computer Algorithms Bayes Theorem Uncertainty
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Two-dimensional materials-based probabilistic synapses and reconfigurable neurons for measuring inference uncertainty using Bayesian neural networks.

Nature communications Oct 17, 2022
Artificial neural networks have demonstrated superiority over traditional computing architectures in tasks such as pattern classification and learning. However, they do not measure uncertainty in predictions, and hence they can make wrong predictions...
Bayes Theorem Neurons Synapses Neural Networks, Computer Uncertainty
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Estimation of Parameters on Probability Density Function Using Enhanced GLUE Approach.

Computational intelligence and neuroscience Oct 14, 2022
The most essential process in statistical image and signal processing is the parameter estimation of probability density functions (PDFs). The estimation of the probability density functions is a contentious issue in the domains of artificial intelli...
Bayes Theorem Probability Algorithms Artificial Intelligence Likelihood Functions Computer Simulation
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Multi-Task Assignment Method of the Cloud Computing Platform Based on Artificial Intelligence.

Computational intelligence and neuroscience Oct 13, 2022
To realize load balancing of cloud computing platforms in big data processing, the method of finding the optimal load balancing physical host in the algorithm cycle is adopted at present. This optimal load balancing strategy that overly focuses on th...
Big Data Artificial Intelligence Bayes Theorem Cloud Computing Algorithms
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Online eye-movement classification with temporal convolutional networks.

Behavior research methods Oct 11, 2022
The simultaneous classification of the three most basic eye-movement patterns is known as the ternary eye-movement classification problem (3EMCP). Dynamic, interactive real-time applications that must instantly adjust or respond to certain eye behavi...
Bayes Theorem Movement Neural Networks, Computer Eye Movements Humans
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Trainable Quaternion Extended Kalman Filter with Multi-Head Attention for Dead Reckoning in Autonomous Ground Vehicles.

Sensors (Basel, Switzerland) Oct 11, 2022
Extended Kalman filter (EKF) is one of the most widely used Bayesian estimation methods in the optimal control area. Recent works on mobile robot control and transportation systems have applied various EKF methods, especially for localization. Howeve...
Lasers Attention Robotics Bayes Theorem Algorithms
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Clustering of trauma patients based on longitudinal data and the application of machine learning to predict recovery.

Scientific reports Oct 10, 2022
Predicting recovery after trauma is important to provide patients a perspective on their estimated future health, to engage in shared decision making and target interventions to relevant patient groups. In the present study, several unsupervised tech...
Cluster Analysis Bayes Theorem Risk Factors Supervised Machine Learning Humans Machine Learning
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Using Artificial Intelligence for Predicting the Duration of Emergency Evacuation During Hospital Fire.

Disaster medicine and public health preparedness Oct 10, 2022
OBJECTIVE: A danger threatening hospitals is fire. The most important action following a fire is to urgently evacuate the hospital during the shortest time possible. The aim of this study was to predict the duration of emergency evacuation following ...
Artificial Intelligence Machine Learning Humans Hospitals Algorithms Bayes Theorem
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Inferring Effective Connectivity Networks From fMRI Time Series With a Temporal Entropy-Score.

IEEE transactions on neural networks and learning systems Oct 5, 2022
Inferring brain-effective connectivity networks from neuroimaging data has become a very hot topic in neuroinformatics and bioinformatics. In recent years, the search methods based on Bayesian network score have been greatly developed and become an e...
Time Factors Magnetic Resonance Imaging Neural Networks, Computer Brain Nerve Net Entropy Brain Mapping Bayes Theorem
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