Abstract
The recognition of Oracle Bone Inscriptions(OBIs) is of great significance to archaeology, history, and linguistics. To realize the fast and accurate retrieval of images for large-scale OBIs datasets and break through the limitations of current conventional retrieval methods, this paper proposes a convolutional neural network for OBIs recognition. The model is designed according to the characteristics of OBIs. The experimental results show that the improved network can better extract the features of OBIs characters, and the recognition rate reaches 84.45%, which is 13.74% higher than the network before the improvement.
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Acknowledgment
The authors acknowledge the supports from the National Natural Science Foundation of China (No. U1804153, 61806007), the Oracle Bone Inscriptions Research and Application Special Project of Ministry of Education and National Language Committee of China (No. YWZ-J010, YWZ-J023), the National Social Science Fund Major Entrusted Project of China (No. 16@ZH017A3), the Program for Changjiang Scholars and Innovative Research Team in University (No. 2017PT35), the Development Projects of Henan Province Science and Technology(No. 202102310562).
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Liu, M., Gao, F., Li, B., Liu, G. (2021). Application of Neural Network in Oracle Bone Inscriptions. In: Xing, C., Fu, X., Zhang, Y., Zhang, G., Borjigin, C. (eds) Web Information Systems and Applications. WISA 2021. Lecture Notes in Computer Science(), vol 12999. Springer, Cham. https://doi.org/10.1007/978-3-030-87571-8_41
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DOI: https://doi.org/10.1007/978-3-030-87571-8_41
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