FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging
Doyen Sahoo, Wang Hao, Shu Ke, Wu Xiongwei, Hung Le, Palakorn, Achananuparp, Ee-Peng Lim, Steven C. H. Hoi

TL;DR
FoodAI leverages deep learning for accurate food image recognition to facilitate convenient and effective food logging, aiding health management and lifestyle improvements, especially tailored for Singaporean cuisine.
Contribution
The paper introduces FoodAI, a deep learning-based food recognition system trained on 400,000 images across 756 classes, integrated into a practical health app ecosystem.
Findings
High accuracy in recognizing diverse Singaporean foods
Over 100 organizations actively use the FoodAI API
Contributed to improved food logging and health monitoring
Abstract
An important aspect of health monitoring is effective logging of food consumption. This can help management of diet-related diseases like obesity, diabetes, and even cardiovascular diseases. Moreover, food logging can help fitness enthusiasts, and people who wanting to achieve a target weight. However, food-logging is cumbersome, and requires not only taking additional effort to note down the food item consumed regularly, but also sufficient knowledge of the food item consumed (which is difficult due to the availability of a wide variety of cuisines). With increasing reliance on smart devices, we exploit the convenience offered through the use of smart phones and propose a smart-food logging system: FoodAI, which offers state-of-the-art deep-learning based image recognition capabilities. FoodAI has been developed in Singapore and is particularly focused on food items commonly consumed…
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