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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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Prif Awduron: Bezuglova, E. S., Безуглова, Е. С., Shiriaev, E. M., Ширяев, Е. М., Kucherov, N. N., Кучеров, Н. Н., Valuev, G. V., Валуев, Г. В.
Fformat: Статья
Iaith:English
Cyhoeddwyd: Springer Science and Business Media Deutschland GmbH 2022
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Mynediad Ar-lein:https://dspace.ncfu.ru/handle/20.500.12258/19624
Tagiau: Ychwanegu Tag
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id ir-20.500.12258-19624
record_format dspace
spelling 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
institution СКФУ
collection 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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