Image classification is the task of assigning an input image, a single label drawn from a fixed set of categories. Image classification models are trained and evaluated on large classification datasets such as ImageNet that has 1000 image categories.
A very popular model that is often used as a backbone CNN to extract visual representations. It achieves a Top 1 accuracy of 76.1 on ImageNet (1000 categories).
Achieves a very impressive Top 1 accuracy of 79.3 on ImageNet (1000 categories).
A lean mobile network that achieves a Top 1 accuracy of 72.0 on ImageNet (1000 categories) with just 3.4 Million parameters