Very interesting approach and perhaps a good step towards transliteration and translation of cuneiform tablets. Code and links for paper at https://github.com/TAU-VAILab/ProtoSnap/tree/main
So ideally the ml network would solve the problem end to end but these authors seem to be using a network for only one step of their otherwise classic image processing pipeline
A lot of applied work in vision and audio glues together different existing modules, instead of training the whole thing end-to-end.
In an ideal world, things are ideal. But the world isn't a grad student's wet dream.
But there are not as many influential papers in the world as there are people who respond: "Why didn't they train the whole thing end-to-end?"