AIMC Topic: Stochastic Processes

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Computer Vision in Monitoring Fruit Browning: Neural Networks vs. Stochastic Modelling.

Sensors (Basel, Switzerland) Apr 15, 2025
As human labour is limited and therefore expensive, computer vision has emerged as a solution with encouraging results for monitoring and sorting tasks in the agrifood sector, where conventional methods for inspecting fruit browning that are generall...
Neural Networks, Computer Bayes Theorem Humans Stochastic Processes Pyrus Color Fruit
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A machine learning computational approach for the mathematical anthrax disease system in animals.

PloS one Apr 1, 2025
OBJECTIVES: The current research investigations present the numerical solutions of the anthrax disease system in animals by designing a machine learning stochastic procedure. The mathematical anthrax disease system in animals is classified into susce...
Anthrax Bacillus anthracis Algorithms Animals Bayes Theorem Stochastic Processes Machine Learning
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Control of medical digital twins with artificial neural networks.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Mar 13, 2025
The objective of precision medicine is to tailor interventions to an individual patient's unique characteristics. A key technology for this purpose involves medical digital twins, computational models of human biology that can be personalized and dyn...
Humans Neural Networks, Computer Uncertainty Models, Biological Stochastic Processes Computer Simulation Precision Medicine
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Loss formulations for assumption-free neural inference of SDE coefficient functions.

NPJ systems biology and applications Mar 1, 2025
Stochastic differential equations (SDEs) are one of the most commonly studied probabilistic dynamical systems, and widely used to model complex biological processes. Building upon the previously introduced idea of performing inference of dynamical sy...
Stochastic Processes Neural Networks, Computer Algorithms Computer Simulation
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A novel intelligent framework for assessing within-host transmission dynamics of Chikungunya virus using an unsupervised stochastic neural network approach.

Computational biology and chemistry Feb 20, 2025
In this study, we present a novel intelligent computing framework based on unsupervised random projection neural networks for analyzing the within-host transmission dynamics of the Chikungunya virus with an adaptive immune response. In addition to th...
Neural Networks, Computer Stochastic Processes Chikungunya virus Chikungunya Fever Humans
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Practical X-ray gastric cancer diagnostic support using refined stochastic data augmentation and hard boundary box training.

Artificial intelligence in medicine Feb 1, 2025
Endoscopy is widely used to diagnose gastric cancer and has a high diagnostic performance, but it must be performed by a physician, which limits the number of people who can be diagnosed. In contrast, gastric X-rays can be taken by radiographers, thu...
Stomach Neoplasms Deep Learning Humans Machine Learning Radiographic Image Interpretation, Computer-Assisted Stochastic Processes
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Probabilistic-sampling-based asynchronous control for semi-Markov jumping neural networks with reaction-diffusion terms.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2024
This paper investigates the probabilistic-sampling-based asynchronous control problem for semi-Markov reaction-diffusion neural networks (SMRDNNs). Aiming at mitigating the drawback of the well-known fixed-sampling control law, a more general probabi...
Probability Markov Chains Neural Networks, Computer Algorithms Computer Simulation Stochastic Processes
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Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP.

Neural networks : the official journal of the International Neural Network Society Dec 7, 2024
Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networks with similar learning abilities remains a challenge. In particular, it is unresolved how differen...
gamma-Aminobutyric Acid Stochastic Processes Action Potentials Neurons Neuronal Plasticity Neural Networks, Computer Models, Neurological Learning Humans
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Data-dependent stability analysis of adversarial training.

Neural networks : the official journal of the International Neural Network Society Dec 4, 2024
Stability analysis is an essential aspect of studying the generalization ability of deep learning, as it involves deriving generalization bounds for stochastic gradient descent-based training algorithms. Adversarial training is the most widely used d...
Humans Stochastic Processes Neural Networks, Computer Algorithms Deep Learning
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Delayed-feedback oscillators replicate the dynamics of multiplex networks: Wavefront propagation and stochastic resonance.

Neural networks : the official journal of the International Neural Network Society Nov 30, 2024
The widespread development and use of neural networks have significantly enriched a wide range of computer algorithms and promise higher speed at lower cost. However, the imitation of neural networks by means of modern computing substrates is highly ...
Feedback Time Factors Neural Networks, Computer Stochastic Processes Algorithms Computer Simulation
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