摘要
Abstract
Oracle bone inscriptions are the source of Chinese characters and the root of Chinese excellent traditional culture.Because oracle rubbings are artificially carved and buried deep underground,they have some problems such as uneven sample distribution and serious noise,resulting in low recognition accuracy.To solve the above problems,we propose an oracle bone character recognition method based on FM-MobileViT(Fusion and Attention Mechanism MobileViT)network.Firstly,the image in the dataset is sharpened and preprocessed to make the target edge more clear and obvious.The image corresponding to the character category with too little data is enhanced by random rotation and random miscut,which improves the quality of the data set and enriches the sample data.Secondly,the fusion module is designed,the jump connection structure is built,and the deep and shallow features are fused,so that the extracted feature map can integrate the shallow features and semantic features.The CBAM attention mechanism is introduced into the fusion module to make the fusion operation more directional and purposeful,and enhance the ability of feature extraction.Ablation and comparison experiments show that the recognition accuracy of the FM-MobileViT model proposed reaches 92.3％,1.7 percentage points higher than that of MobileViT,and the FPS reaches 30 107.Compared with the same type of network structure,FM-MobileViT not only has a higher accuracy,but also achieves a trade-off between accuracy and speed.关键词
甲骨文字拓片/MobileViT/文字识别/深度学习/融合模块/注意力机制Key words
rubbings of oracle bone character/MobileViT/character recognition/deep learning/fusion module/attention mechanism分类
计算机与自动化
