A NOVEL DATASET FOR VIETNAMESE NEW YEAR FOOD CLASSIFICATION

A NOVEL DATASET FOR VIETNAMESE NEW YEAR FOOD CLASSIFICATION

Food classification has always piqued the interest of both domestic and international researchers, but numerous challenges remain. We present the dataset UIT-TASTET21, which contains over 77,000 color images of 18 traditional Vietnamese Lunar New Year dishes. We have experimented with classification...

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書誌詳細
主要な著者: Vo, Duy Nguyen, Ngo, Van Tan Luu, Le, Thi Phuong Vy, Van, Nguyen Ngoc Huyen, Nguyen, Duc Anh Phuc, Ngo, Van Tuan Kiet, Truong, Thanh Thang, Pham, Tan Tai, Dinh, Nhat Minh, Ho, Thai Ngoc, Nguyen, Tan Tran Minh Khang
フォーマット: 論文
言語:English
出版事項: Trường Đại học Đà Lạt 2024
主題:
Convolutional neural network (CNN)
Deep feature
Food classification
Tet holiday
オンライン･アクセス:https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/256906
https://tckh.dlu.edu.vn/index.php/tckhdhdl/article/view/989
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Thư viện lưu trữ: Thư viện Trường Đại học Đà Lạt
その他の書誌記述
要約:Food classification has always piqued the interest of both domestic and international researchers, but numerous challenges remain. We present the dataset UIT-TASTET21, which contains over 77,000 color images of 18 traditional Vietnamese Lunar New Year dishes. We have experimented with classification using feature vectors from network architectures such as VGG16, Inception-v3, ResNet-50, Xception, and MobileNet-v2 to train support vector machines (SVMs), meeting the dataset’s challenges and laying the groundwork for the development of many optimal methods in the future that promise scientific breakthroughs in the service and commercial industries. At the same time, the authors desire to share a piece of Vietnamese cuisine’s distinctiveness with worldwide friends.

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