Optimization of ancient Chinese characters recognition in particular conditions

Document Type

Conference Proceeding

Publication Date

1-1-2023

Abstract

This paper discusses optimization of ancient Chinese characters recognition in particular conditions. It aims to improve the image recognition technique exerted on ancient Chinese text. During the process, we first use images under good conditions to train the model, AlexNet and ResNet, and predict the input images. Assuming the accuracy rate is over 70%, the image is identified as one in good condition. Then, the results of the models are used as output. If the accuracy does not achieve the expected rate, the images will be filtered and inputted into the models trained by the filtered picture in bad condition to predict. After several epochs of training the two models, ResNet is more appropriate for the process discussed above. Due to its high accuracy of 89%, ResNet is chosen as the model being used in the recognition process. Overall, ancient Chinese characters recognition is improved by process mentioned above.

Identifier

85176500126 (Scopus)

ISBN

[9781510668621]

Publication Title

Proceedings of SPIE the International Society for Optical Engineering

External Full Text Location

https://doi.org/10.1117/12.3009377

e-ISSN

1996756X

ISSN

0277786X

Volume

12803

This document is currently not available here.

Share

COinS