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Analysis of Finite Fluctuations as a Basis of Defining a Set of Neural Network Model InputsThe paper describes an approach on the defining a set of neural network model inputs analyzing
Machine learning methods for modeling the kinetics of combustion in problems of space safety. The results of the obtained neural network showed that the presented model is capable of approximating
Neural network technologies and topological analysis of social media data of the integration of neural network and mathematical models for solving such tasks. Mathematical models are built
Estimation of geomagnetic and solar indices by global ionospheric maps with use of neural networks is used as a regression model. The obtained neural network estimates show a high degree of correlation
Neural Network Self-Learning Model for Complex Assessment of Drinking Water Safety for Consumers assessment of the safety of drinking water, the method of clustering was chosen, namely, the neural network
Convolutional Neural Networks for Image Steganalysis computer vision problems. One of these models—Convolutional Neural Network—has been proven to be very
НЕЙРОННЫЕ СЕТИ КАК ИНСТРУМЕНТ ИНТЕЛЛЕКТУАЛЬНОГО МОДЕЛИРОВАНИЯ ОБРАЗОВАТЕЛЬНОЙ СРЕДЫ neural networks. Also it has been released of aspects of artificial neural networks applying for decision
Compressing a convolution neural network based on quantizationModern deep neural network models contain a large number of parameters and have a significant size
Neural network analog of the ICP algorithm. For those tasks, it is more appropriate to use neural network technique and deep learning methods
Generating Graphs With Specified Properties And Their Use For Constructing Scene Graphs From Images, and network modeling. This article
provides three graph generation models and also proposes the
idea
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