Paper Title: Nutrition Assistance Application Using Deep Learning Algorithm

Author's name: Karishma Beevi N, Umamaheswari G

Proper nutrition is crucial for maintaining good health. While nutrition apps exist to help people monitor their food intake and make healthier choices, they often require manual input and can be prone to errors. This paper proposes a real-time image-detecting nutrition value app that uses a deep learning convolutional neural network(CNN) algorithm to automatically analyze the nutritional content of food in real time.A three-layer CNN algorithm was developed to detect food objects and analyze their nutritional content, including calories, fat, and protein. The proposed web app model was tested using a dataset of 5025 food images with manually annotated nutritional values.The CNN model achieved an accuracy rate of 96% in detecting food images and predicting their nutritional content. The proposed app could provide real-time nutrition information for a variety of foods, including pre-packaged foods and restaurant meals.The proposed real-time image-based nutrition assistance app has the potential to help people make more informed food choices and improve their overall health. Further research is needed to refine the model and improve its accuracy, as well as to test its usability and effectiveness in a real-world setting.

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