# How to go about classifying 1000 classes?

I am trying to find research paper with theory(preferably implementation) that is about classifying 1000 (or more) classes. I have heard of an implementation, that initially clustering needs to be done then classification with something like softmax. Does anyone know of any research paper that implements 1000+ class classification.

If you are asking for arbitrary ML task dealing with 1000+ classes the most straigtforward thing that comes to mind is the ImageNet - https://en.wikipedia.org/wiki/ImageNet#cite_note-nytimes_2012-2. It has more the 20k categories in the present time.
The first neural network to tackle this problem was AlexNet and since then plethora of architectures : VGG's, ResNet's, EfficientNet got better and better quality.