Cover Image

Development of a Cluster with Cloud Computing Based on Neural Networks With Deep Learning for Modeling Multidimensional Fields

Saved in:

Bibliographic Details
Date:	2021
Main Authors:	M. Kosovets, L. Tovstenko
Format:	Article
Language:	English
Published:	2021
Series:	Cybernetics and Computer Technologies
Online Access:	http://jnas.nbuv.gov.ua/article/UJRN-0001353859
Tags:	Add Tag No Tags, Be the first to tag this record!
Journal Title:	Library portal of National Academy of Sciences of Ukraine \| LibNAS

Institution

Library portal of National Academy of Sciences of Ukraine | LibNAS

Similar Items

Image segmentation of clouds based on deep learning
by: B. P. Rusyn, et al.
Published: (2020)

Structural and Parametric Synthesis of Deep Learning Neural Networks
by: V. M. Syniehlazov, et al.
Published: (2020)

Deep neural network based on generalized neo-fuzzy neurons and its learning based on backpropagation
by: Ye. V. Bodianskyi, et al.
Published: (2021)

Artificial intelligence in cloud-based mobile radar computing
by: Коsovets, M., et al.
Published: (2023)

Analyzing the models of speech recognition on the basis of neural networks of deep learning for examination of digital phonograms
by: V. I. Solovev, et al.
Published: (2021)

APPLICATION OF DEEP LEARNING NEURAL NETWORK FOR CLASSIFICATION OF BIG DATA OF ASTRONOMIC OBSERVATIONS
by: Gorbunov, A. A., et al.
Published: (2017)

Application of Deep Learning Neural Network for Classification of Big Data of Astronomic Observations
by: A. A. Gorbunov, et al.
Published: (2017)

On Biomedical Computations in Cluster and Cloud Environment
by: T. Bardadym, et al.
Published: (2021)

Neural networks’ learning process acceleration
by: Katerynych, L., et al.
Published: (2020)

Neural networks’ learning process acceleration
by: Katerynych, L., et al.
Published: (2020)

Developing a semantic image model using machine learning based on convolutional neural networks
by: P. I. Andon, et al.
Published: (2020)

Developing a semantic image model using machine learning based on convolutional neural networks
by: Andon, P.I., et al.
Published: (2020)

Formal verification of deep neural networks
by: Panchuk, B.O.
Published: (2024)

Practical content of the elements of petrophysical model of terrigenous sandstones — oil and gas reservoirs in neural networks, deep learning and regression methods
by: Vyzhva, Serhiy, et al.
Published: (2025)

Two dimensional model of learning in spiking neural networks with homeostasis and reward
by: V. M. Osaulenko
Published: (2017)

Increasing the reliability of mobile intelligent machines based on deep neural networks
by: S. V. Kovalevskyi, et al.
Published: (2018)

Synthesis of optimal structure of deep neural network
by: Yu. Koval, et al.
Published: (2016)

System aspects of design guaranteased cloud calculations
by: Kosovets, N.A., et al.
Published: (2018)

System aspects of design guaranteased cloud calculations
by: N. A. Kosovets, et al.
Published: (2018)

Neural networks&#039; learning process acceleration
by: L. Katerynych, et al.
Published: (2020)

Mathematical and Computer Modeling of Soil Contamination in Halych District Based on the Theory of Neural Networks
by: Horbiychuk, M.I., et al.
Published: (2015)

Mathematical and Computer Modeling of Soil Contamination in Halych District Based on the Theory of Neural Networks
by: M. I. Horbiychuk, et al.
Published: (2015)

Deep neural network elements and their implementation in FPGA Xilinx
by: T. A. Samoliuk
Published: (2015)

Evaluation of the Features Significance Based on Neural Networks in Tasks of the Analysis of the Distance Learning Quality
by: E. M. Filonenko, et al.
Published: (2018)

An Artificial Neural Networks Modeling Environment for Solving a Clustering Task
by: Yu. V. Moskalenko
Published: (2019)

The cloud-based component to support the process of informatics discipline learning
by: I. A. Bezverbnyi
Published: (2018)

Automatic development of deep neural networks for improving numerical meteorological forecast
by: Doroshenko, А.Yu., et al.
Published: (2024)

To the issue of optimizing cloud computing based on their cost
by: Doroshenko, А.Yu., et al.
Published: (2021)

To the issue of optimizing cloud computing based on their cost
by: Yu. Doroshenko, et al.
Published: (2020)

Methods of artificial intelligence for acoustic emission diagnostics of fracture stages (A review). P. 2: Artificial neural network and deep learning
by: O. M. Stankevych, et al.
Published: (2024)

Compression Methods of Deep Learning Models Based on Student-Teacher Method
by: I. V. Stetsenko, et al.
Published: (2019)

Improving face recognition models using convolutional neural networks, metric learning and optimization methods
by: A. M. Litvynchuk, et al.
Published: (2021)

Enhancing image inpainting through image decomposition and deep neural networks
by: K. Bellaj, et al.
Published: (2023)

Clusterization of associative network based on polynomially computable spectral invariants of graphs
by: Ju. A. Kulakov, et al.
Published: (2014)

Neural networks application for cluster analysis of the healthcare system crisis
by: I. A. Markina, et al.
Published: (2016)

Self-learning neural network technologies in the systems of structural recognition of visual objects
by: Berestovskii, A. E., et al.
Published: (2015)

Study of stochastic gradient methods for optimization of algorithms of learning artificial neural networks
by: T. A. Samoljuk
Published: (2017)

Neural network technologies to processing natural language texts in adaptive learning systems
by: I. M. Domanetska, et al.
Published: (2017)

System of automatic segmentation of pauses in phonograms on the basis of neuron networks of the deep learning
by: V. I. Solovev, et al.
Published: (2021)

Grid and cloud computing for the modeling of the motion of a magnetized symmetric body in an external magnetic field
by: S. I. Ljashko, et al.
Published: (2016)