For the widely used handwriting dataset, MNIST, there is a site that actively tracks the best algorithms (although I'm not sure when it was last updated): http:

For the widely used handwriting dataset, MNIST, there is a site that actively tracks the best algorithms (although I'm not sure when it was last updated): http://rodrigob.github.io/are_we_there_yet/build/classification_datasets_results.html http://rodrigob.github.io/are_we_there_yet/build/classificat... You'll notice that all of the top contenders use Neural Networks, but I would bet that many of them use at least some traditional CV techniques to transform the images at various steps. That said, many of the more modern deep learning approaches are ditching CV altogether, just feeding in raw pixels without any normalization or transformation, leaving fewer parameters to tweak.