The segmented UEC Food-100 dataset with benchmark experiment on food detection

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dc.authoridBattini Sonmez, Elena/0000-0003-0090-984X|batur, okan zafer/0000-0002-1585-1794
dc.authorwosidBattini Sonmez, Elena/AAZ-6358-2021
dc.authorwosidbatur, okan zafer/L-3251-2018
dc.contributor.authorSonmez, Elena Battini
dc.contributor.authorMemis, Sefer
dc.contributor.authorArslan, Berker
dc.contributor.authorBatur, Okan Zafer
dc.date.accessioned2024-07-18T20:40:37Z
dc.date.available2024-07-18T20:40:37Z
dc.date.issued2023
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractAutomatic food classification systems have several interesting applications ranging from detecting eating habits, to waste food management and advertisement. When a food image has multiple food items, the food detection step is necessary before classification. This work challenges the food detection issue and it introduces to the research community the Segmented UEC Food-100 dataset, which expands the original UEC Food-100 database with segmentation masks. In the semantic segmentation experiment, the performance of YOLAC and DeeplabV3+ has been compared and YOLAC reached the best accuracy of 64.63% mIoU. In the instance segmentation experiment, YOLACT has been used due to its speed and high accuracy. The benchmark performance on the newly released Segmented UEC Food-100 dataset is 68.83% mAP. For comparison purpose, experiments have been run also on the UEC FoodPix Complete dataset of Okamoto et al. The database and the code will be available after publication.en_US
dc.identifier.doi10.1007/s00530-023-01088-9
dc.identifier.endpage2057en_US
dc.identifier.issn0942-4962
dc.identifier.issn1432-1882
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85152358394en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2049en_US
dc.identifier.urihttps://doi.org/10.1007/s00530-023-01088-9
dc.identifier.urihttps://hdl.handle.net/11411/7142
dc.identifier.volume29en_US
dc.identifier.wosWOS:000968175900001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofMultimedia Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSegmented Uec Food-100 Databaseen_US
dc.subjectFood Detectionen_US
dc.subjectSemantic Segmentationen_US
dc.subjectInstance Segmentationen_US
dc.titleThe segmented UEC Food-100 dataset with benchmark experiment on food detectionen_US
dc.typeArticleen_US

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