DEVELOPMENT OF A PROGRESSIVE WEB APPLICATION WITH A CONVOLUTIONAL NEURAL NETWORK FOR IMAGE RECOGNITION

Authors

  • Maria Volodymyrivna Baraban Vinnytsia National Technical University
  • Serhii Volodymyrovych Baraban Vinnytsia National Technical University
  • Volodymyr Volodymyrovych Garmash Vinnytsia National Technical University

DOI:

https://doi.org/10.31649/1999-9941-2021-50-1-7-14

Keywords:

Progressive Web App, web application, convolutional neural network, image recognition

Abstract

In this paper the technologies for creating web applications are analyzed, in result Progressive Web App as the most suitable for solving the tasks is selected. The peculiarities of the use of intelligent technologies for the problem of image recognition are investigated. Emphasis is placed on methods that use the TensorFlow neural network library. The own model of convolutional neural network for image recognition has been created. The dataset «The Quick, Draw! Dataset» from Google is selected for model training. It has been determined that a progressive web application provides the ability to provide the resulting sample to the user faster than analogues. The result of comparing the speed of the developed and analog applications is illustrated.

Author Biographies

Maria Volodymyrivna Baraban, Vinnytsia National Technical University

Ph.D., Associate Professor of Automation and Intelligent Information Technologies

Serhii Volodymyrovych Baraban, Vinnytsia National Technical University

Ph.D., Associate Professor, Associate Professor of Computer Science

Volodymyr Volodymyrovych Garmash, Vinnytsia National Technical University

Ph.D., Associate Professor, Associate Professor of the Department of Automation and Intelligent Information Technologies

References

Making Progressive Web Apps (PWAs) with React, 2019. [Online]. Available: https://alligator.io/react/react-progressive-web-apps/. Accessed on: February 01, 2021.

Prohresyvnyi veb-zastosunok, 2018. [Elektronnyi resurs]. Rezhym dostupu: https://en.wikipedia.org/wiki/Progressive_Web_Apps. Data zvernennia: Liut. 01, 2021.

Progressive Web, 2018. [Online]. Available: https://codelabs. developers.google.com/codelabs/your-first-pwapp-ru/index.html?index=..%2F..%2Flangru#0. Accessed on: February 01, 2021.

M. D. Zeiler, R. Fergus, «Visualizing and understanding convolutional networks», in European confer-ence on computer vision, Springer International Publishing, pp. 818–833, 2014.

Fei-Fei Li, A. Karpathy, J. Johnson, CS231n Convolutional Neural Networks for Visual Recognition, 2016. [Online]. Available: https://cs231n.github.io/convolutional-networks. Accessed on: Mar. 21, 2017.

T. O. Kovtun, M. V. Baraban, V. V. Harmash, «Prohresyvnyi veb dodatok dlia rozpiznavannia maliunkiv» na XV Mizhnarodnii naukovii konferentsii «Kontrol i upravlinnia v skladnykh systemakh», Vinnytsia: VNTU, 8–10 zhovtnia, 2020. [Elektronnyi resurs]. Rezhym dostupu: https://conferences.vntu.edu.ua/index.php/mccs/mccs2020/paper/view/10665. Data zvernennia: Liut. 01, 2021.

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Abstract views: 423

Published

2021-04-19

How to Cite

[1]
M. V. Baraban, S. V. Baraban, and V. V. Garmash, “DEVELOPMENT OF A PROGRESSIVE WEB APPLICATION WITH A CONVOLUTIONAL NEURAL NETWORK FOR IMAGE RECOGNITION”, ІТКІ, vol. 50, no. 1, pp. 7–14, Apr. 2021.

Issue

Vol. 50 No. 1 (2021): Information technology and computer engineering

Section

Information technology and coding theory

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