Because they don't get to see the entire letter shapes. The page at [0] shows the basic idea: they're forced to make decisions based on each part of each stroke of the letter. If they were heavily overfitting on the strokes of the letters in the training sample, then they'd be so inaccurate outside the sample that the assembled outputs would hardly resemble letters at all, much less words.
(Also, this is heavily-damaged handwriting, not clear print, so each letter isn't even uniform in shape. A model trying to cheat at ink detection would have an uphill battle trying to guess what all the variant letter shapes might be.)
(Also, this is heavily-damaged handwriting, not clear print, so each letter isn't even uniform in shape. A model trying to cheat at ink detection would have an uphill battle trying to guess what all the variant letter shapes might be.)
[0] https://scrollprize.org/grandprize#how-accurate-are-these-pi...