Food Image Classi cation Using Convolutional Neural Network

Abstract

In our thesis we tried to classify food images using convolutional neural network. Convolutional neural network extracts spatial features from images so it is very e cient to use convolutional neural network for image clasi cation problem. Recently people are sharing food images in social media and writing review on food. So there is a lot of food image but some image may not be labeled. It will be very helpful for restaurants if they can advertise their food to those people who is looking similar kind of foods they o er. Food classi cation system can help social media platform to identify food. Food classi cation system can enable an opportunity for social media platform to o er advertisement service for restaurants and beverage companies to their targeted users. It will be nancially bene cial for both social media platform and beverage companies. Food classi cation is very di cult task because there is high variance in same category of food images. We developed a convolutional neural network model to classify food images in food-11 dataset. We also used transfer learning technique using Inception V3.