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Layering Images with Convolution Neural Networks on Cloud Computing

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Nature of Computation and Communication (ICTCC 2022)

Abstract

Artificial neural networks combined with deep learning (DL) techniques are becoming a very powerful tool that gives the best performance for many difficult problems such as: the speech recognition, the image recognition, etc. the language processing. The training of the neural network models takes place in many different languages, different techniques, different sizes of organizations. However, previous studies only focused on the model training techniques, the datasets, currently there is no research that fully introduces running artificial neural network models, the network models are run in the cloud connecting directly from RStudio. In this article, we focus on creating models and applying deep learning models of the artificial neural networks based on the cloud computing, in order to create a separate research direction. The results of this study open up a new approach to cloud-based deep learning programming, providing an additional choice of the deep learning approaches for those wishing to enter the field.

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Correspondence to Hiep Xuan Huynh .

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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Van Nguyen, T., Tran, L.K., Tran, T.C.T., Huynh, H.X. (2023). Layering Images with Convolution Neural Networks on Cloud Computing. In: Phan, C.V., Nguyen, T.D. (eds) Nature of Computation and Communication. ICTCC 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 473. Springer, Cham. https://doi.org/10.1007/978-3-031-28790-9_11

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  • DOI: https://doi.org/10.1007/978-3-031-28790-9_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-28789-3

  • Online ISBN: 978-3-031-28790-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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