Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12258/19624
Title: An overview of the methods used to recognize garbage
Authors: Bezuglova, E. S.
Безуглова, Е. С.
Shiriaev, E. M.
Ширяев, Е. М.
Kucherov, N. N.
Кучеров, Н. Н.
Valuev, G. V.
Валуев, Г. В.
Keywords: Convolutional neural networks;Deep learning;Household garbage;Machine vision;Mineral recognition;Solid household waste
Issue Date: 2022
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: 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
Series/Report no.: Lecture Notes in Networks and Systems
Abstract: 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
URI: http://hdl.handle.net/20.500.12258/19624
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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