Recognition of Online Turkish Handwriting using Transfer Learning

Authors : Esma Fatıma BİLGİN TAŞDEMİR

Pages : 719-726

Doi:10.29109/gujsc.1141508

View : 33 | Download : 35

Publication Date : 2023-09-27

Article Type : Research Paper

Abstract :We present a recognition system for online Turkish handwriting using transfer learning. Training deep networks requires large amounts of data. Since such a sufficiently large collection of Turkish handwriting samples is not available, So we adopt the transfer learning approach and train and optimize a CNN-BLSTM recognition system first using the standard IAM-On dataset of English handwriting. Then, we fine tune it with Turkish handwriting samples from a smaller dataset. Fine tuning increases the character recognition rate of the final system which is evaluated on 2,041 samples of isolated Turkish words from the initial value of 49% to 85%. The results show that transfer learning can be a solution to the data scarcity problem of online Turkish handwriting.
Keywords : Online Handwriting Recognition, Deep Learning, Transfer Learning, Turkish Handwriting Recognition