Image Recognition with Deep Learning

Abstract

Image recognition is one of the most important fields of image processing and computer vision. Food image classification is an unique branch of image recognition problem. In modern days people are more conscious about their health. A system that can classify food from image is necessary for a dietary assessment system. Classification of food images is very challenging since the dataset of food images is highly non-linear. In this paper we proposed a method that can classify food categories with images. We used convolutional neural network to classify food images. The CNNs are a very effective class of neural networks that is highly effective at the task of image classifying, object detection and other computer vision problems. We classified a food dataset consisting different food categories with 16643 images. We obtained an accuracy of 92.86% in our experiment.