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Machine Learning Methods and Models for Recognizing Lung Inhomogeneity from Computed Tomography Scans
Shakhmametova, G. R., Stepanova, E. S., Akhmetshin, A. A., Zulkarneev, R. Kh.
The article considers the use of deep neural networks for the recognition of lungs inhomogeneity
Creation of A Fuzzy Neural Networks to Assess Environmental Safety
Panischev O.Y., Ahmedshina E.k., Kataseva D.V., Katasev A.S., Akhmetvaleev A.M.
the process of training fuzzy neural networks forming a model of a collective of fuzzy neural networks and a
Integration of the Russian Stock Market with Systems of Artificial Neural Network and Their Applications
Perez D.C., Murtuzalieva S.Y.
to model a large system of neural networks to integrate and control all Russian stock markets. This model
Integration of the Russian Stock Market with Systems of Artificial Neural Network and Their Applications
Perez D.C., Murtuzalieva S.Y.
to model a large system of neural networks to integrate and control all Russian stock markets. This model
Pairing an arbitrary regressor with an artificial neural network estimating aleatoric uncertainty
Gurevich P., Stuke H.
in regression tasks performed by artificial neural networks. It is based on the simultaneous training of two
Reduction of neural network models in intelligent computer systems of a new generation
Kroshchanka, A.
Reduction of neural network models in intelligent computer systems of a new generation
Voice Detection Using Convolutional Neural Network
Vishniakou, U. A., Shaya, B. H.
technologies for convolutional neural network and its use for voice (cough) recognition. Tasks of article
Patterns of electrical activity generated by biological neural network in vitro
Denisov, A. A., Bulai, P. M., Pitlik, T. N., Molchanov, P. G., Cherenkevich, S. N., Pashkevich, S. G., Dosina, M. O.
biological neural net- work developing in fully artificial conditions. This is a promising model for study
Modeling of internal combustion engines by adaptive network-based fuzzy inference system
are necessary for the implementation of the control action. The structure of the neural network and the rules
Emergence of the small-world architecture in neural networks by activity dependent growth
Gafarov F.
and development of neural networks based on the latest achievements of experimental neuroscience. The model

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