11–17 of 17 posts
Nice! Is it trained on Latin character-based hand writing only, or can it also predict other charactersets?
[1] http://www.fki.inf.unibe.ch/databases/iam-handwriting-databa...
Earlier quoted context omitted.
How much computing power/time did it take to train the model? Had any hyperparameters optimization been done? Sorry if I missed the reference that has this information, but I think that these numbers are important in any deep learning experiment because they allow the readers to evaluate applicability of described methods to their problems.
This post has more details about the model: http://blog.otoro.net/2015/12/12/handwriting-generation-demo...
There is work being done on explaining non-linear models, such as LIME [1], but much more is needed. At a recent d3 meetup the topic was discussed but we primarily noted its importance. Notes at [2].
[1] https://github.com/marcotcr/lime [2] https://docs.google.com/document/d/1o-DO65PEZShLuadyRd35PsTJ...
Earlier quoted context omitted.
I'm doing some research into handwriting recognition. In particular transcribing older documents. Do you see a way of applying your work here in that direction?
The generative model of handwriting that we're working with here probably isn't very applicable to handwriting recognition. In principle, you could train a model like this to jointly model the text and the produced handwriting and then search for the most likely text to correspond to handwriting, but it would be a lot less efficient and likely not work as well. Instead, the natural way to apply neural networks to use…
And the kind of activity display you did later also works.
We're slowly coming to an era where everything can be easily forged.