Abstract

Food monitoring and nutritional analysis play a crucial role in addressing allergen-related health issues, and their importancecontinues to grow in our daily lives. In this study, we utilizeda convolutional neural network (CNN) to recognize and analyze food images, assess the nutritional content of dishes, and provide information on potential allergens. Identifying food items from images poses a significant challenge due to the wide variety of foods available. To address this, we leveraged the Logmeal API, which utilizes CNN to identify various types of meals, their ingredients, and potential allergens.

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