Food Image Classification Using Deep Learning Techniques - 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. The classification of food images is a very difficult task as the dataset of food images is highly non-linear. In this paper, we proposed a method that can classify food images. We used pre trained models for the food image classification. The pre trained models is based on the convolutional neural network. In neural networks the CNNs is highly effective at the task of image classification and other computer vision problem. We classified a food image dataset i.e. food11 and obtained an accuracy of 96.75% in our experiment.