An overview of the methods used to recognize garbage
This article offers an overview of methods employed to recognize garbage. There are methods discussed, which rely on machine vision to detect objects, as well as hardware for garbage sorting intelligence systems. There has been a comparative analysis carried out, which embraces various methods based...
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Springer Science and Business Media Deutschland GmbH
2022
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ir-20.500.12258-196242022-05-26T12:02:43Z An overview of the methods used to recognize garbage Bezuglova, E. S. Безуглова, Е. С. Shiriaev, E. M. Ширяев, Е. М. Kucherov, N. N. Кучеров, Н. Н. Valuev, G. V. Валуев, Г. В. Convolutional neural networks Deep learning Household garbage Machine vision Mineral recognition Solid household waste This article offers an overview of methods employed to recognize garbage. There are methods discussed, which rely on machine vision to detect objects, as well as hardware for garbage sorting intelligence systems. There has been a comparative analysis carried out, which embraces various methods based on machine vision and optical sensors aimed at detecting metal in garbage. There have been technologies identified, which feature the best ratio of indicators. The main criteria included the cost of building a system based on the method, and accuracy. Further on, there are plans to carry out research focusing on developing an original system for the recognition of garbage patterns, its classification and sorting 2022-05-26T12:01:58Z 2022-05-26T12:01:58Z 2022 Статья Bezuglova, E., Shiriaev, E., Kucherov, N., Valuev, G. An overview of the methods used to recognize garbage // Lecture Notes in Networks and Systems. - 2022. - Том 424. - Стр.: 467 - 478. - DOI10.1007/978-3-030-97020-8_42 http://hdl.handle.net/20.500.12258/19624 en Lecture Notes in Networks and Systems application/pdf Springer Science and Business Media Deutschland GmbH |
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Репозиторий |
language |
English |
topic |
Convolutional neural networks Deep learning Household garbage Machine vision Mineral recognition Solid household waste |
spellingShingle |
Convolutional neural networks Deep learning Household garbage Machine vision Mineral recognition Solid household waste Bezuglova, E. S. Безуглова, Е. С. Shiriaev, E. M. Ширяев, Е. М. Kucherov, N. N. Кучеров, Н. Н. Valuev, G. V. Валуев, Г. В. An overview of the methods used to recognize garbage |
description |
This article offers an overview of methods employed to recognize garbage. There are methods discussed, which rely on machine vision to detect objects, as well as hardware for garbage sorting intelligence systems. There has been a comparative analysis carried out, which embraces various methods based on machine vision and optical sensors aimed at detecting metal in garbage. There have been technologies identified, which feature the best ratio of indicators. The main criteria included the cost of building a system based on the method, and accuracy. Further on, there are plans to carry out research focusing on developing an original system for the recognition of garbage patterns, its classification and sorting |
format |
Статья |
author |
Bezuglova, E. S. Безуглова, Е. С. Shiriaev, E. M. Ширяев, Е. М. Kucherov, N. N. Кучеров, Н. Н. Valuev, G. V. Валуев, Г. В. |
author_facet |
Bezuglova, E. S. Безуглова, Е. С. Shiriaev, E. M. Ширяев, Е. М. Kucherov, N. N. Кучеров, Н. Н. Valuev, G. V. Валуев, Г. В. |
author_sort |
Bezuglova, E. S. |
title |
An overview of the methods used to recognize garbage |
title_short |
An overview of the methods used to recognize garbage |
title_full |
An overview of the methods used to recognize garbage |
title_fullStr |
An overview of the methods used to recognize garbage |
title_full_unstemmed |
An overview of the methods used to recognize garbage |
title_sort |
overview of the methods used to recognize garbage |
publisher |
Springer Science and Business Media Deutschland GmbH |
publishDate |
2022 |
url |
https://dspace.ncfu.ru/handle/20.500.12258/19624 |
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