计算机技术与发展2024，Vol.34Issue(10)：46-52,7.DOI:10.20165/j.cnki.ISSN1673-629X.2024.0181
基于改进DenseNet的西夏文识别研究
Study on Recognition of Xixia Text Based on Improved DenseNet
摘要
Abstract
Due to a large number of strokes,complex structure,high similarity,and the problems of missing characters,foxing,and fading in the ancient books of Xixia,it is still a difficult research to detect and recognize them at present,and the existing recognition studies mostly have problems such as suboptimal recognition accuracy,omission,misdiagnosis.Therefore,we propose an improved DenseNet-based Xixia text recognition method based on a comprehensive analysis of the current mainstream research.The proposed method replaces the traditional 3×3 convolution in the original model by introducing the spatial and channel reconstruction convolution,which mainly utilizes the channel reconstruction module and the spatial reconstruction module to reduce the redundancy between the feature maps in the training process of the network,and improves the feature representation capability of the network.Furthermore,it uses the mutual-channel loss instead of the cross-entropy loss in the loss function part,which further reduces the feature redundancy and improves the ability of the network to focus on the key recognition regions without introducing any external parameters.The results of the comparison experiments show that the accuracy of the proposed method is 97.08%and the parameters are 6.2 MB on 668 types of Xixia text recognition datasets,which is a more obvious improvement relative to the current mainstream methods,proving its effectiveness.关键词
西夏古籍/文字识别/通道重建/空间重构/互通道损失Key words
ancient books of Xixia/text recognition/channel reconstruction/spatial reconstruction/mutual-channel loss分类
信息技术与安全科学引用本文复制引用
岳霄,景诗云,史伟..基于改进DenseNet的西夏文识别研究[J].计算机技术与发展,2024,34(10):46-52,7.基金项目
国家自然科学基金项目(62166030,12061055) （62166030,12061055）
