Abstract
The process of classifying many types of food from images is an exciting field involving various applications. Especially in tourist, Vietnamese food classification connects us across our cultures and generations. Food classification is not easy, even with people. The reason is the food's extreme diversity between dishes and in the middle variations of the dish. So some traditional approaches with hand-crafted features had been used for food recognition. However, evaluation in deep learning and convolutional neural networks achieved higher accuracy compared to the traditional methods. We propose a new dataset called TypicalVietnameseFoodNet and a proposed model with the best performance for our dataset, called the TypicalVietnameseFood model. Our proposed approach achieves 94.84% on the test set.
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