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| Дата публикации | Название | Авторы |
| 2023 | Assessing the Mass Transfer Coefficient in Jet Bioreactors with Classical Computer Vision Methods and Neural Networks Algorithms | Nizovtseva, I.; Palmin, V.; Simkin, I.; Starodumov, I.; Mikushin, P.; Nozik, A.; Hamitov, T.; Ivanov, S.; Vikharev, S.; Zinovev, A.; Svitich, V.; Mogilev, M.; Nikishina, M.; Kraev, S.; Yurchenko, S.; Mityashin, T.; Chernushkin, D.; Kalyuzhnaya, A.; Blyakhman, F. |
| 2018 | Building extraction from satellite imagery using a digital surface model | Dunaeva, A. V.; Kornilov, F. A. |
| 2019 | Comparison of UNet, ENet, and BoxENet for Segmentation of Mast Cells in Scans of Histological Slices | Karimov, A.; Razumov, A.; Manbatchurina, R.; Simonova, K.; Donets, I.; Vlasova, A.; Khramtsova, Y.; Ushenin, K. |
| 2021 | Computer vision system for the automatic asbestos content control in stones | Zyuzin, V.; Ronkin, M.; Porshnev, S.; Kalmykov, A. |
| 2023 | Data-Driven Machine Learning Methods for Nontechnical Losses of Electrical Energy Detection: A State-of-the-Art Review | Pazderin, A.; Kamalov, F.; Gubin, P. Y.; Safaraliev, M.; Samoylenko, V.; Mukhlynin, N.; Odinaev, I.; Zicmane, I. |
| 2022 | Deep Machine Learning Potentials for Multicomponent Metallic Melts: Development, Predictability and Compositional Transferability | Ryltsev, R. E.; Chtchelkatchev, N. M. |
| 2021 | Deepfake: эволюция фейка как угроза медиасреде | Чертов, Д. А.; Chertov, D. A. |
| 2023 | Enhancing seismic design of non-structural components implementing artificial intelligence approach: Predicting component dynamic amplification factors | Bhavani, B. D.; Challagulla, S. P.; Noroozinejad, Farsangi, E.; Hossain, I.; Manne, M. |
| 2021 | Generation of echocardiographic 2D images of the heart using cGAN | Zyuzin, V.; Komleva, J.; Porshnev, S. |
| 2023 | Implication of radiation on the thermal behavior of a partially wetted dovetail fin using an artificial neural network | Nimmy, P.; Nagaraja, K. V.; Srilatha, P.; Karthik, K.; Sowmya, G.; Kumar, R. S. V.; Khan, U.; Hussain, S. M.; Hendy, A. S.; Ali, M. R. |
| 2023 | Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on k-Means and k-Nearest Neighbors Algorithms | Matrenin, P. V.; Khalyasmaa, A. I.; Gamaley, V. V.; Eroshenko, S. A.; Papkova, N. A.; Sekatski, D. A.; Potachits, Y. V. |
| 2019 | Machine learning in the processing and analysis of texts | Ptukhin, A. A.; Khrushkov, A. E.; Bozhko, E. M.; Птухин, А. А.; Хрушков, А. Е.; Божко, Е. М. |
| 2014 | Methods of neural networks and pattern recognition and theirs applications to economy, engineering, and medicine | Мазуров, Вл. Д.; Смирнов, А. И.; Mazurov, Vl. D.; Smirnov, A. I. |
| 2020 | Modeling of changes in heat resistance of nickel-based alloys using bayesian artificial neural networks | Anoshina, O. V.; Trubnikova, A. S.; Milder, O. B.; Tarasov, D. A.; Ganeev, A. A.; Tyagunov, A. G. |
| 2022 | Modeling the influence of the composition of refractory elements on the heat resistance of nickel alloys by a deep learning artificial neural network | Tarasov, D. A.; Milder, O. B.; Tiagunov, A. G. |
| 2023 | Noise-induced complex dynamics and synchronization in the map-based Chialvo neuron model | Bashkirtseva, I.; Ryashko, L.; Used, J.; Seoane, J. M.; Sanjuán, M. A. F. |
| 2018 | Nonlinear mean-field dynamo and prediction of solar activity | Safiullin, N.; Kleeorin, N.; Porshnev, S.; Rogachevskii, I.; Ruzmaikin, A. |
| 2023 | Operational Forecasting of Wind Speed for an Self-Contained Power Assembly of a Traction Substation | Matrenin, P. V.; Khalyasmaa, A. I.; Rusina, A. G.; Eroshenko, S. A.; Papkova, N. A.; Sekatski, D. А. |
| 2022 | Prediction of Sandstone Dilatancy Point in Different Water Contents Using Infrared Radiation Characteristic: Experimental and Machine Learning Approaches | Ma, L.; Khan, N. M.; Cao, K.; Rehman, H.; Salman, S.; Rehman, F. U. |
| 2021 | A Proposed ANN-Based Acceleration Control Scheme for Soft Starting Induction Motor | Menaem, A. A.; Elgamal, M.; Abdel-Aty, A. -H.; Mahmoud, E. E.; Chen, Z.; Hassan, M. A. |
