Prediction of Probable Allergens in Food Items Using Convolutional Neural Networks


Authors : Harshavardan. R.; Kanish. S.; Madhav Suta Adityan. G; Rathi Gopalakrishnan

Volume/Issue : Volume 9 - 2024, Issue 4 - April

Google Scholar : https://tinyurl.com/yc7w8wud

Scribd : https://tinyurl.com/4cccz3x5

DOI : https://doi.org/10.38124/ijisrt/IJISRT24APR921

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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.

Keywords : Convolutional Neural Network (CNN), Food Image Recognition, Convolution Layers, Nutrition,Logmeal API,Food Allergies

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.

Keywords : Convolutional Neural Network (CNN), Food Image Recognition, Convolution Layers, Nutrition,Logmeal API,Food Allergies

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