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Chinese inscription restoration based on artificial intelligent models

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Publicado en:Heritage Science vol. 13, no. 1 (Dec 2025), p. 326
Autor principal: Wang, Zhen
Otros Autores: Li, Yujun, Li, Honglei
Publicado:
Springer Nature B.V.
Materias:
Calligraphy
Machine learning
Accuracy
Deep learning
Artificial intelligence
Books
Neural networks
Image restoration
Computer vision
Natural language processing
Image quality
Inscriptions
Cultural resources
Cultural heritage
Acceso en línea:Citation/Abstract
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Resumen:Chinese ancient inscriptions have a long history, while natural erosion and human destruction have led to many incomplete inscriptions with low-quality textual data and blurry images. With deep learning technologies, it is expected to use relevant image and language processing tasks to restore inscriptions. To improve the efficiency of restoration tasks and promote the digital protection of cultural heritage, this study used deep learning technology to restore ancient Chinese inscriptions. We combined natural language processing and computer vision technologies to train models for restoring inscriptions. The results indicated that the joint solution had advantages over every single model for incomplete character restoration.
ISSN:2050-7445
DOI:10.1038/s40494-025-01900-x
Fuente:Materials Science Database