Performance analysis of chinese cursive character recognition based on convolutional neural network

Chinese cursive characters written in old books are more difficult to recognize than other Chinese Characters such as handwritten Chinese character because they have many various styles. For this reason, it needs a software-based recognition model or service that can recognize Chinese cursive character more easily to assist and support many related researchers. In this paper, we will show the performance analysis results of Chinese cursive character recognition based on Convolutional Neural Network (CNN). In the performance evaluation, we used a dataset collected directly from many old books. Data augmentation technique was applied because our dataset is relatively small dataset when compared to other deep learning datasets. Our optimized recognition model showed about 91.6% recognition accuracy.