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A Food Recommendation System Combining InceptionV3 and KNN Considering Calorie Estimated From Images

Dhali, Debratna (2021) A Food Recommendation System Combining InceptionV3 and KNN Considering Calorie Estimated From Images. Masters thesis, Dublin, National College of Ireland.

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Abstract

Dietitians and nutritionists have a major concern about the eating habits of people especially at a time when obesity and non-communicable diseases due to unhealthy eating habits are on the rise across the globe. The improvement of computational power provides an opportunity to automate the process of assessing the food intake of people. Rather than the regular monitoring practices, an automated process of doing this is more convenient and the same is proposed in this research. A computer vision based system is proposed in this research to detect the food item and estimate the overall calorie intake using the features extracted from pretrained InceptionV3 algorithm, a process which in machine learning is referred to as transfer learning. Nutritionix database has been webscraped to construct the dataset containing nutritional information of the detected food items. To further enhance the system, K-nearest neighbors algorithm has been implemented to develop a recommender system that suggests alternatives of the detected food items. The proposed image classification model is mainly evaluated against metrics like training and validation accuracy and train and validation loss. These solutions are aimed at addressing the problems of time consumption, imprecision, under reporting etc. which can occur with traditional monitoring processes.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Computer vision; Deep Learning; Image Classification; Food Detection; Web Scraping; Calorie Estimation; Recommender System; KNN
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software

R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine > Personal Health and Hygiene
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Clara Chan
Date Deposited: 20 Nov 2021 11:50
Last Modified: 20 Nov 2021 11:50
URI: https://norma.ncirl.ie/id/eprint/5145

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