Food-Classification

This project focuses on the development and imple�mentation of a classification system for food identification. Automatic food identification can assist with food intake monitoring to maintain a healthy diet. Food classification is a challenging problem due to the large number of food categories, high visual similarity between different food categories, as well as the lack of datasets that are large enough for training deep models. The project explores two different approaches. In the first one, I use an SVM after the computation of BoW(computed with SIFT), while in the second approach, I use a custom CNN trained on the original data.