An Automated Image-Based Dietary Assessment System for Mediterranean Foods.

ABSTRACT: Goal: The modern way of living has significantly influenced the daily diet. The ever-increasing number of people with obesity, diabetes and cardiovascular diseases stresses the need to find tools that could help in the daily intake of the necessary nutrients. Methods: In this paper, we present an automated image-based dietary assessment system of Mediterranean food, based on: 1) an image dataset of Mediterranean foods, 2) on a pre-trained Convolutional Neural Network (CNN) for food image classification, and 3) on stereo vision techniques for the volume and nutrition estimation of the food. We use a pre-trained CNN in the Food-101 dataset to train a deep learning classification model employing our dataset Mediterranean Greek Food (MedGRFood). Based on the EfficientNet family o

SUBMITTER: Konstantakopoulos FS 

PROVIDER: S-EPMC10202193 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature