A Comparative Study of Deep Learning Methods on Food Classification Problem

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dc.authorscopusid57220962993
dc.authorscopusid57220954985
dc.authorscopusid24824171900
dc.authorscopusid36782998200
dc.contributor.authorMemis, S.
dc.contributor.authorArslan, B.
dc.contributor.authorBatur, O.Z.
dc.contributor.authorSonmez, E.B.
dc.date.accessioned2024-07-18T20:17:02Z
dc.date.available2024-07-18T20:17:02Z
dc.date.issued2020
dc.description2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020 -- 15 October 2020 through 17 October 2020 -- -- 165305en_US
dc.description.abstractThis paper gives a comparative study on the performances of several deep learning methods for the food images recognition challenge. The experiments were conducted on the UEC Food-100 dataset using ResNet-18, Inception-V3, Resnet-50, Densenet-121, Wide Resnet-50 and ResNext-50 with images of size 320x320 and 299x299. The limited size of the database required the transfer learning approach; that is, all models were trained with pretrained ImageNet weights. The best classification result was obtained using ResNext-50 with 87.7 % accuracy. © 2020 IEEE.en_US
dc.identifier.doi10.1109/ASYU50717.2020.9259904
dc.identifier.isbn9781728191362
dc.identifier.scopus2-s2.0-85097962100en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ASYU50717.2020.9259904
dc.identifier.urihttps://hdl.handle.net/11411/6386
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassificationen_US
dc.subjectDeep Learningen_US
dc.subjectDenseneten_US
dc.subjectInceptionen_US
dc.subjectMachine Learningen_US
dc.subjectResneten_US
dc.subjectResnexten_US
dc.subjectUec Food 100en_US
dc.subjectIntelligent Systemsen_US
dc.subjectLearning Systemsen_US
dc.subjectTransfer Learningen_US
dc.subjectClassification Resultsen_US
dc.subjectComparative Studiesen_US
dc.subjectFood İmageen_US
dc.subjectLearning Methodsen_US
dc.subjectDeep Learningen_US
dc.titleA Comparative Study of Deep Learning Methods on Food Classification Problemen_US
dc.typeConference Objecten_US

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