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Junya Liu

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Proceedings Article | 27 March 2024 Paper

Oracle recognition based on improved YOLOv7

Junya Liu, Ting Huang, Rujia Li, Zhen Yang

Proceedings Volume 13105, 1310523 (2024) https://doi.org/10.1117/12.3026793

KEYWORDS: Bone, Education and training, Deep learning, Matrices, Machine learning, Detection and tracking algorithms, Object recognition, Object detection, Image processing, Data processing

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To realize the automatic recognition of oracle bones, this paper presents an oracle bone recognition technology based on the development of Chinese characters. In the experimental process, the model of YOLOv7 algorithm is used to realize the recognition function of oracle script. The model of YOLOv7 algorithm is improved by adding the Coordconv structure and replacing the traditional NMS (Non-maximum Suppression) with the matrix NMS, which effectively improves the recognition accuracy and speed of the oracle script. Moreover, in this work, oracle recognition is introduced based on the semi-supervised learning of training, learning, Jinwen, the relationship between the seal script and the clerical script, and more script features are used to search existing words. In the experiment, the recognition accuracy of the oracle script reached 81.12%. This also proved that there is a certain relationship between the oracle script characters in the process of evolution, which is a basis for the research of oracle script characters based on the evolution of Chinese characters.

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