Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/20.500.12258/19624
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dc.contributor.authorBezuglova, E. S.-
dc.contributor.authorБезуглова, Е. С.-
dc.contributor.authorShiriaev, E. M.-
dc.contributor.authorШиряев, Е. М.-
dc.contributor.authorKucherov, N. N.-
dc.contributor.authorКучеров, Н. Н.-
dc.contributor.authorValuev, G. V.-
dc.contributor.authorВалуев, Г. В.-
dc.date.accessioned2022-05-26T12:01:58Z-
dc.date.available2022-05-26T12:01:58Z-
dc.date.issued2022-
dc.identifier.citationBezuglova, 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_42ru
dc.identifier.urihttp://hdl.handle.net/20.500.12258/19624-
dc.description.abstractThis 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 sortingru
dc.language.isoenru
dc.publisherSpringer Science and Business Media Deutschland GmbHru
dc.relation.ispartofseriesLecture Notes in Networks and Systems-
dc.subjectConvolutional neural networksru
dc.subjectDeep learningru
dc.subjectHousehold garbageru
dc.subjectMachine visionru
dc.subjectMineral recognitionru
dc.subjectSolid household wasteru
dc.titleAn overview of the methods used to recognize garbageru
dc.typeСтатьяru
vkr.instФакультет математики и компьютерных наук имени профессора Н.И. Червяковаru
vkr.instСеверо-Кавказский центр математических исследованийru
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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