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Singapore has been striving to improve the provision of healthcare servicesto her people. In this course, the government has taken note of the deficiencyin regulating and supervising people's nutrient intake, which is identified asa contributing factor to the development of chronic diseases. Consequently,this issue has garnered significant attention. In this paper, we share ourexperience in addressing this issue and attaining medical-grade nutrient intakeinformation to benefit Singaporeans in different aspects. To this end, wedevelop the FoodSG platform to incubate diverse healthcare-orientedapplications as a service in Singapore, taking into account their sharedrequirements. We further identify the profound meaning of localized fooddatasets and systematically clean and curate a localized Singaporean fooddataset FoodSG-233. To overcome the hurdle in recognition performance broughtby Singaporean multifarious food dishes, we propose to integrate supervisedcontrastive learning into our food recognition model FoodSG-SCL for theintrinsic capability to mine hard positive/negative samples and therefore boostthe accuracy. Through a comprehensive evaluation, we present performanceresults of the proposed model and insights on food-related healthcareapplications. The FoodSG-233 dataset has been released inhttps://foodlg.comp.nus.edu.sg/.

From Plate to Prevention: A Dietary Nutrient-aided Platform for Health Promotion in Singapore