Review of Modern Technologies of Computer Vision

Today, the use of artificial intelligence technologies is becoming more and more popular. Scientific and technological progress contributes to increasing the power of hardware, as well as obtaining effective methods for implementing methods such as machine learning, neural networks, and deep learnin...

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Bibliografische gegevens
Hoofdauteurs:	Bezuglova, E. S., Безуглова, Е. С., Gladkov, A. V., Гладков, А. В., Valuev, G. V., Валуев, Г. В.
Formaat:	Статья
Taal:	English
Gepubliceerd in:	2023
Onderwerpen:	Artificial intelligence OpenCV Computer vision Convolutional neural networks ResNet YOLO
Online toegang:	https://dspace.ncfu.ru/handle/20.500.12258/25243
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spelling	ir-20.500.12258-252432023-09-08T07:58:42Z Review of Modern Technologies of Computer Vision Bezuglova, E. S. Безуглова, Е. С. Gladkov, A. V. Гладков, А. В. Valuev, G. V. Валуев, Г. В. Artificial intelligence OpenCV Computer vision Convolutional neural networks ResNet YOLO Today, the use of artificial intelligence technologies is becoming more and more popular. Scientific and technological progress contributes to increasing the power of hardware, as well as obtaining effective methods for implementing methods such as machine learning, neural networks, and deep learning. This created the possibility of creating effective methods for recognizing images and video data, which is what computer vision is. At the time of 2022, a huge number of methods, technologies, and techniques for using computer vision were received, in this paper a study was conducted on the use of computer vision in 2022. Results were obtained on the decrease in the popularity of computer vision in the scientific community, its introduction into industry, medicine, zoology and human social life, the most popular method of computer vision is the ResNet neural network model. 2023-09-08T07:57:45Z 2023-09-08T07:57:45Z 2023 Статья Bezuglova, E., Gladkov, A., Valuev, G. Review of Modern Technologies of Computer Vision // Lecture Notes in Networks and Systems. - 2023. - 702 LNNS, pp. 321-331. - DOI: 10.1007/978-3-031-34127-4_31 http://hdl.handle.net/20.500.12258/25243 en Lecture Notes in Networks and Systems application/pdf
institution	СКФУ
collection	Репозиторий
language	English
topic	Artificial intelligence OpenCV Computer vision Convolutional neural networks ResNet YOLO
spellingShingle	Artificial intelligence OpenCV Computer vision Convolutional neural networks ResNet YOLO Bezuglova, E. S. Безуглова, Е. С. Gladkov, A. V. Гладков, А. В. Valuev, G. V. Валуев, Г. В. Review of Modern Technologies of Computer Vision
description	Today, the use of artificial intelligence technologies is becoming more and more popular. Scientific and technological progress contributes to increasing the power of hardware, as well as obtaining effective methods for implementing methods such as machine learning, neural networks, and deep learning. This created the possibility of creating effective methods for recognizing images and video data, which is what computer vision is. At the time of 2022, a huge number of methods, technologies, and techniques for using computer vision were received, in this paper a study was conducted on the use of computer vision in 2022. Results were obtained on the decrease in the popularity of computer vision in the scientific community, its introduction into industry, medicine, zoology and human social life, the most popular method of computer vision is the ResNet neural network model.
format	Статья
author	Bezuglova, E. S. Безуглова, Е. С. Gladkov, A. V. Гладков, А. В. Valuev, G. V. Валуев, Г. В.
author_facet	Bezuglova, E. S. Безуглова, Е. С. Gladkov, A. V. Гладков, А. В. Valuev, G. V. Валуев, Г. В.
author_sort	Bezuglova, E. S.
title	Review of Modern Technologies of Computer Vision
title_short	Review of Modern Technologies of Computer Vision
title_full	Review of Modern Technologies of Computer Vision
title_fullStr	Review of Modern Technologies of Computer Vision
title_full_unstemmed	Review of Modern Technologies of Computer Vision
title_sort	review of modern technologies of computer vision
publishDate	2023
url	https://dspace.ncfu.ru/handle/20.500.12258/25243
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Review of Modern Technologies of Computer Vision

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