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Improving the Food classification rate using Transfer Learning methods

Rane, Dhanashree Subhash (2022) Improving the Food classification rate using Transfer Learning methods. Masters thesis, Dublin, National College of Ireland.

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Abstract

Nowadays due to growing food consumption and variance in dietary behaviour, the diet may get imbalanced. The mainstream part of the diet is the calorie intake, which shall be taken care of. To appropriately assess and monitor the diet, various advanced learning frameworks have been incorporated. Therefore, in our study, we have introduced a food classification model which will recognize the food product and state the calories of each. For this, we have utilized the DNN algorithms such as Mobile Net V2, Inception V3, and Custom Architecture. Each of these algorithms is evaluated and the optimal algorithms based on performance are considered for further implementation. The application for this model can be widened with the growing technological advances.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QP Physiology > Nutrition
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 08 Mar 2023 17:29
Last Modified: 08 Mar 2023 17:29
URI: https://norma.ncirl.ie/id/eprint/6281

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