{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T19:15:45Z","timestamp":1779218145301,"version":"3.51.4"},"reference-count":21,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,5,4]],"date-time":"2021-05-04T00:00:00Z","timestamp":1620086400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Polish Ministry of Science and Higher Education","award":["020\/RID\/2018\/19),"],"award-info":[{"award-number":["020\/RID\/2018\/19),"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Computational Intelligence and Soft Computing"],"published-print":{"date-parts":[[2021,5,4]]},"abstract":"<jats:p>Plastic waste management is a challenge for the whole world. Manual sorting of garbage is a difficult and expensive process, which is why scientists create and study automated sorting methods that increase the efficiency of the recycling process. The plastic waste may be automatically chosen on a transmission belt for waste removal by using methods of image processing and artificial intelligence, especially deep learning, to improve the recycling process. Waste segregation techniques and procedures are applied to major groups of materials such as paper, plastic, metal, and glass. Though, the biggest challenge is separating different materials types in a group, for example, sorting different colours of glass or plastics types. The issue of plastic garbage is important due to the possibility of recycling only certain types of plastic (PET can be converted into polyester material). Therefore, we should look for ways to separate this waste. One of the opportunities is the use of deep learning and convolutional neural network. In household waste, the most problematic are plastic components, and the main types are polyethylene, polypropylene, and polystyrene. The main problem considered in this article is creating an automatic plastic waste segregation method, which can separate garbage into four mentioned categories, PS, PP, PE-HD, and PET, and could be applicable on a sorting plant or home by citizens. We proposed a technique that can apply in portable devices for waste recognizing which would be helpful in solving urban waste problems.<\/jats:p>","DOI":"10.1155\/2021\/6626948","type":"journal-article","created":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T19:26:06Z","timestamp":1620242766000},"page":"1-7","source":"Crossref","is-referenced-by-count":87,"title":["Deep Learning for Plastic Waste Classification System"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3345-604X","authenticated-orcid":true,"given":"Janusz","family":"Bobulski","sequence":"first","affiliation":[{"name":"Czestochowa University of Technology, Department of Computer Science, Cz\u0119stochowa, Poland"}]},{"given":"Mariusz","family":"Kubanek","sequence":"additional","affiliation":[{"name":"Czestochowa University of Technology, Department of Computer Science, Cz\u0119stochowa, Poland"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejpe.2018.07.003\u201d"},{"key":"2","article-title":"Problemy gospodarki odpadami w polsce","author":"J. Radziewicz","year":"2019"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.wasman.2016.09.015"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.wasman.2015.10.034"},{"key":"5","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.1109\/CISP.2010.5647729","article-title":"Intelligent solid waste processing using optical sensor based sorting technology","volume":"4","author":"J. Huang","year":"2010","journal-title":"Image and Signal Processing (CISP)"},{"key":"6","first-page":"695","article-title":"Advanced waste-splitting by sensor based sorting on the example of the MTPlant oberlaa","volume":"10","author":"S. Pieber","year":"2010","journal-title":"Tagungsband Zur"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.conbuildmat.2014.09.109"},{"key":"8","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-52881-6_7","article-title":"Case study: interpretability of fuzzy systems applied to nonlinear modelling and control","volume-title":"Design of Interpretable Fuzzy Systems. Studies in Computational Intelligence,","author":"K. Cpa\u0142ka","year":"2017"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1117\/1.jei.21.1.013018"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1016\/j.rti.2005.04.003"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/j.wasman.2010.06.023"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.2174\/1876400201003010056"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1016\/j.wasman.2011.06.007"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.resconrec.2012.01.007"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1016\/j.wasman.2014.06.015"},{"key":"16","first-page":"1368","article-title":"Deep: convolutional neural network applies to face recognition in small and medium databases","author":"M. Wang"},{"key":"17","volume-title":"Deep Learning","author":"I. Goodfellow","year":"2016"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-014-0405-7"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68720-9_8"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20518-8_30"},{"key":"21","article-title":"CNN use for plastic garbage classification method","author":"J. Bobulski"}],"container-title":["Applied Computational Intelligence and Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2021\/6626948.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2021\/6626948.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2021\/6626948.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T19:26:13Z","timestamp":1620242773000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/acisc\/2021\/6626948\/"}},"subtitle":[],"editor":[{"given":"Miin-Shen","family":"Yang","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,5,4]]},"references-count":21,"alternative-id":["6626948","6626948"],"URL":"https:\/\/doi.org\/10.1155\/2021\/6626948","relation":{},"ISSN":["1687-9732","1687-9724"],"issn-type":[{"value":"1687-9732","type":"electronic"},{"value":"1687-9724","type":"print"}],"subject":[],"published":{"date-parts":[[2021,5,4]]}}}