Food Classification Using Deep Learning Method: A Review

Abstract

Image classification has become less complicated with deep learning and availability of larger datasets and computational assets. The Convolution neural network is the most popular and extensively used image classification technique in the latest days. Image classification is performed on diverse food dataset using various transfer learning techniques. The food plays a vital role in human’s life as it provides us different nutrients and consequently it is necessary for every individual to maintain a watch on their eating habits. Therefore, food classification is a quintessential thing for a healthier lifestyle. Unlike the traditional methods of building a model from the scratch, pre trained models are used in this project which saves the computation time and cost and also has given better results. The food dataset of many classes with many images in each class is used for training and validating. Using these pre-trained models, the given food will be recognized, and the nutrient content will be predicted based on the colour in the image.