Displaying 1 to 6 from 6 results

OpenBoard - Interactive whiteboard for schools and universities

  •    C++

OpenBoard is an open source cross-platform interactive white board application designed primarily for use in schools. It was originally forked from Open-Sankoré, which was itself based on Uniboard. It is a tool that can help you do your job and does not get in the way. Use a pen tablet, an interactive whiteboard or even a mouse to write and annotate your course.

sigver_wiwd - Learned representation for Offline Handwritten Signature Verification

  •    Jupyter

This repository contains the code and instructions to use the trained CNN models described in [1] to extract features for Offline Handwritten Signatures. It also includes the models described in [2] that can generate a fixed-sized feature vector for signatures of different sizes. We tested the code in Ubuntu 16.04. This code can be used with or without GPUs - to use a GPU with Theano, follow the instructions in this link. Note that Theano takes time to compile the model, so it is much faster to instantiate the model once and run forward propagation for many images (instead of calling many times a script that instantiates the model and run forward propagation for a single image).

topokanji - Topologically ordered lists of kanji for effective learning

  •    Javascript

It is also smart to learn more common kanji first. This project is based on those two ideas and provides properly ordered lists of kanji to make your learning process as fast, simple, and effective as possible.

han - Using Tensorflow to train a model to detect miswritten Chinese characters.

  •    Python

Han is a deep-learning project dealing with misspelled handwriting Chinese characters. Its primary purpose is to find out the misspelled Chinese characters written by professional Chinese font designers, to review the result.

Chilanka - Chilanka handwriting style Malayalam font

  •    HTML

Chilanka is Malayalam handwriting style font designed by Santhosh Thottingal. Chilanka follows the common style one can see in everyday handwriting of Malayalam. It has a comprehensive Malayalam glyph set that contains most of the unique Malayalam conjuncts. The glyph strokes are of uniform width with round ends giving the impression of written with either a thin felt-tip pen, or a ball-point pen. Sharp corners are completely avoided and gives the fine touch of beautiful curves of Malayalam script. The style is not the handwriting style of designer, but is based on many handwriting samples he observed. A uniform set was selected from them for the font. Even though the style is handwriting, the glyphs follow the horizontal baseline and can be used for body text too.

thai-handwriting-number - Create Thai handwriting number dataset

  •    Python

Feel free to contribute on this project, I will be happy to work with you.