AIMC Topic: Probability

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Noise Immunity and Robustness Study of Image Recognition Using a Convolutional Neural Network.

Sensors (Basel, Switzerland) Feb 6, 2022
The problem surrounding convolutional neural network robustness and noise immunity is currently of great interest. In this paper, we propose a technique that involves robustness estimation and stability improvement. We also examined the noise immunit...
Uncertainty Recognition, Psychology Neural Networks, Computer Image Processing, Computer-Assisted Noise Probability
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Predicting Embryo Viability Based on Self-Supervised Alignment of Time-Lapse Videos.

IEEE transactions on medical imaging Feb 2, 2022
With self-supervised learning, both labeled and unlabeled data can be used for representation learning and model pretraining. This is particularly relevant when automating the selection of a patient's fertilized eggs (embryos) during a fertility trea...
Humans Pregnancy Supervised Machine Learning Probability Time-Lapse Imaging Female ROC Curve
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Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion.

Sensors (Basel, Switzerland) Jan 21, 2022
After lung cancer, breast cancer is the second leading cause of death in women. If breast cancer is detected early, mortality rates in women can be reduced. Because manual breast cancer diagnosis takes a long time, an automated system is required for...
Humans Female Probability Ultrasonography, Mammary Breast Neoplasms Breast Deep Learning
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Using deep learning to predict the outcome of live birth from more than 10,000 embryo data.

BMC pregnancy and childbirth Jan 16, 2022
BACKGROUND: Recently, the combination of deep learning and time-lapse imaging provides an objective, standard and scientific solution for embryo selection. However, the reported studies were based on blastocyst formation or clinical pregnancy as the ...
Datasets as Topic Endpoint Determination Microscopy Probability Single Embryo Transfer Live Birth Time-Lapse Imaging Deep Learning ROC Curve Predictive Value of Tests Area Under Curve Humans Reproducibility of Results
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Effective TCP Flow Management Based on Hierarchical Feedback Learning in Complex Data Center Network.

Sensors (Basel, Switzerland) Jan 13, 2022
Many studies focusing on improving Transmission Control Protocol (TCP) flow control realize a more effective use of bandwidth in data center networks. They are excellent ways to more effectively use the bandwidth between clients and back-end servers....
Deep Learning Probability Humans Algorithms Feedback
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Dissipativity-Based Disturbance Attenuation Control for T-S Fuzzy Markov Jumping Systems With Nonlinear Multisource Uncertainties and Partly Unknown Transition Probabilities.

IEEE transactions on cybernetics Jan 11, 2022
This article is concerned with the dissipativity-based disturbance attenuation control for a class of Takagi-Sugeno (T-S) fuzzy Markov jump systems (FMJSs) suffering from nonlinear multisource disturbances. The considered system possesses nonlinear a...
Algorithms Probability Nonlinear Dynamics Computer Simulation Fuzzy Logic
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Overtaking risk modeling in two-lane two-way highway with heterogeneous traffic environment of a low-income country using naturalistic driving dataset.

Journal of safety research Dec 29, 2021
INTRODUCTION: Driver behavior related to overtaking maneuvers, which are considered a major safety risk determinant on two-lane two-way highway in low- and middle-income countries (LMIC), are an important subject of further analysis. This study evalu...
Automobile Driving Decision Making Probability Accidents, Traffic Humans Logistic Models
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Human Factor Risk Modeling for Shipyard Operation by Mapping Fuzzy Fault Tree into Bayesian Network.

International journal of environmental research and public health Dec 28, 2021
The operational activities conducted in a shipyard are exposed to high risk associated with human factors. To investigate human factors involved in shipyard operational accidents, a double-nested model was proposed in the present study. The modified ...
Accidents Humans Factor Analysis, Statistical Probability Fuzzy Logic Bayes Theorem
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Of research and robots: making sense of chance findings.

BMJ (Clinical research ed.) Dec 16, 2021
Probability Humans Robotics
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DeepCME: A deep learning framework for computing solution statistics of the chemical master equation.

PLoS computational biology Dec 8, 2021
Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogor...
Statistics as Topic Stochastic Processes Models, Chemical Probability Computer Simulation Deep Learning Computational Biology
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