TypicalVietnameseFoodNet:用于越南食品分类的越南食品图像数据集

T. Cao, Khoa Van Duong
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引用次数: 0

摘要

从图像中对多种食物进行分类的过程是一个令人兴奋的领域,涉及各种应用。特别是在旅游中,越南的食物分类将我们跨越文化和世代联系在一起。食物分类并不容易,即使是人。原因是菜肴之间的食物多样性和中间的菜肴变化。因此,一些具有手工特征的传统方法被用于食物识别。然而,与传统方法相比,深度学习和卷积神经网络中的评估获得了更高的准确性。我们提出了一个名为TypicalVietnameseFoodNet的新数据集,以及一个为我们的数据集提供最佳性能的建议模型,称为TypicalVietnameseFood模型。我们提出的方法在测试集上达到了94.84%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TypicalVietnameseFoodNet: A Vietnamese Food Image Dataset For Vietnamese Food Classifications
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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