[kirelabs]

Hi, I am the author. There is actually no HTML5 involved. It's SVG+AJAX on the client side and Ruby on the server side, though a backend written in Haskell is nearly ready to be deployed. Gotta fight some memory leaks before I will switch though. I am planning for client side processing but there is some serious number crunching going on behind the scenes and I am still sceptical if Javascript can do it.

[Robin_Message]

Just wondering how the classifier works. You presumably calculate the probability of each symbol matching the one I have drawn, but I wondered if you did any a priori modelling of the likelihood of me drawing any particular symbol. For example, I went and drew a simple capital theta, and it was number 5 on the list after some fairly esoteric shapes, all with similar shapes. At the point, where there are several very similar shapes, I'd have thought having a good prior distribution helps accuracy more.

Are you using click data to model what people are drawing, or just to retrain the classifier? It's also not totally obvious you should click the right one — I only realised after I started writing this comment.

Also, I noted Greek letters are displayed in italics. Did you train on italics only for? People don't tend to write italics, which might be why Greek letters are not matching well for me.