Handwriting comenia script recognition with convolutional neural network
Martin Rajnoha, Radim Bürget, Malay Kishore Dutta · 2017
This paper deals with handwriting recognition (HWR) using artificial intelligence of so-called Comenia script - a modern handwritten font similar to block letters recently introduced at primary schools in the Czech Republic. This work describes a method how to extend a limited training set of handwritten letters and proposes a new method to increase stability and accuracy by artificially created image samples. We examined a large set of algorithms including a deep learning method for classification of the handwriting characters. The best results were achieved using a convolutional neural network, which achieved the accuracy or character recognition 90.04 %.