Classification of Turkish cuisine with deep learning on mobile platform
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Dosyalar
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In recent years, image classification has been a subject that is often dealt with in computerized vision. This is mainly due to the fact that more accurate results can be achieved in less time by using the classification method. In this study, food classification process has been carried out by using Convolutional Neural Network (CNN) that is frequently preffered deep learning techniques in machine learning issues. According to the obtained results, the highest accuracy rate was obtained by using Stochastic Gradient Descent (SGD) optimization algorithm with Softmax activation function. That accuracy rate was calculated as 93%. A conversion is applied to trained model in order to use in mobile devices. Application was used to recognize food whose photo taken and/or selected. In addition, for food name having the highest recognition percentage; calorie, nutritional values, recipe ingredients and recipe were given. Our study 'Turk Mutfagi' was made ready to applying food classification in iOS devices and usage in daily life.
Açıklama
4th International Conference on Computer Science and Engineering (UBMK) -- SEP 11-15, 2019 -- Samsun, TURKEY
Anahtar Kelimeler
Deep Learning, Food Classification, Convolutional Neural Network, Inceptionv3, iOS
Kaynak
2019 4Th International Conference On Computer Science And Engineering (Ubmk)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
