Food Image Classification Using Machine Learning Techniques: A Review - Baid, Yash; Dhole, Avinash (International Journal of Computer Sciences and Engineering, 2021)
The recognition of image is one of the most important fields in the image processing and computer vision. Image recognition has many branches but the food image classification is very unique. In today’s world people are very conscious about their health. Many people around the world use some dietary assessment system for planning of their diet. In dietary assessment system people make the use of food image classification to classify the food from the image and provide the total amount of calories present in the food. The classification of food images is a very difficult task as the dataset of food images is highly non-linear. In this paper, we are going to use different types of neural network models to show, which neural network provides the best accuracy result in the recognition of food images and is most efficient to use. We are using a food image dataset (food-11) which contains 16643 images in it.