The purpose of this post is to provide a review of the state-of-the-art of image classification algorithms based on the most popular labelled dataset, ImageNet. We will describe some of the innovative architectures which lead to significant improvements. Note that researchers test their algorithms using different datasets (a new ImageNet dataset is released as a new challenge with different images each year). Thus the cited accuracies cannot be directly compared per se.
This blog post is available on Medium.