Deep learning algorithm for dessert recognition and nutritional evaluation

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dc.contributor.authorYusun, Sevilay
dc.contributor.authorYılmaz, Onur
dc.contributor.authorTarlak, Fatih
dc.date.accessioned2025-04-07T12:10:13Z
dc.date.available2025-04-07T12:10:13Z
dc.date.issued2025
dc.departmentFakülteler, Mimarlık ve Tasarım Fakültesi, Gastronomi ve Mutfak Sanatları Bölümü
dc.departmentFakülteler, Mühendislik Fakültesi, Yazılım Mühendisliği Bölümü
dc.description.abstractFood recognition systems are crucial for healthcare and the food industry, aiding in diet tracking, personalised meal planning, and promoting nutritional awareness. This work develops a software interface that recognises food products using deep learning algorithms, and announces their nutritional values and gastronomic characteristics. Specifically, photographs of various desserts were captured in a restaurant setting, and the classification performance of two deep learning models, GoogleNet and ResNet-50, was analysed. Both models achieved high accuracy rates exceeding 99.6 %, with ResNet-50 demonstrating superior performance due to its lower error rates, higher accuracy, and faster learning capabilities. Based on these results, the interface was developed using ResNet-50 to provide consumers with detailed gastronomic information about desserts and support healthier dessert choices. At present, the resulting software is limited to the 23 dessert items on the menu of Healin restaurant (Nisantasi, Istanbul, Turkey), and the way they look in that particular restaurant, but the scope could be expanded in the future. This innovative approach enhances consumer awareness about healthy eating while offering a competitive edge for the food industry by effectively meeting consumer expectations.
dc.description.sponsorshipIstanbul Gedik University
dc.identifier.endpage71
dc.identifier.issn1336-8672
dc.identifier.issue1
dc.identifier.scopus2-s2.0-105001113516
dc.identifier.scopusqualityQ3
dc.identifier.startpage61
dc.identifier.urihttps://hdl.handle.net/11501/2082
dc.identifier.volume64
dc.indekslendigikaynakScopus
dc.institutionauthorYusun, Sevilay
dc.institutionauthorYılmaz, Onur
dc.language.isoen
dc.publisherFood Reseach Institute
dc.relation.ispartofJournal of Food and Nutrition Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDeep Learning Algorithms
dc.subjectDessert Classification
dc.subjectFood Recognition
dc.subjectNutritional Evaluation
dc.titleDeep learning algorithm for dessert recognition and nutritional evaluation
dc.typeArticle

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