Chinese inscription restoration based on artificial intelligent models
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| Publicado en: | Heritage Science vol. 13, no. 1 (Dec 2025), p. 326 |
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| Autor principal: | |
| Otros Autores: | , |
| Publicado: |
Springer Nature B.V.
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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|---|---|---|---|
| 001 | 3227339378 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2050-7445 | ||
| 024 | 7 | |a 10.1038/s40494-025-01900-x |2 doi | |
| 035 | |a 3227339378 | ||
| 045 | 2 | |b d20251201 |b d20251231 | |
| 084 | |a 243040 |2 nlm | ||
| 100 | 1 | |a Wang, Zhen |u Liaoning Normal University, Digital Protection and Utilisation Laboratory of Historical and Cultural Heritage, Dalian, China (GRID:grid.440818.1) (ISNI:0000 0000 8664 1765) | |
| 245 | 1 | |a Chinese inscription restoration based on artificial intelligent models | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Calligraphy | ||
| 653 | |a Machine learning | ||
| 653 | |a Accuracy | ||
| 653 | |a Deep learning | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Books | ||
| 653 | |a Neural networks | ||
| 653 | |a Image restoration | ||
| 653 | |a Computer vision | ||
| 653 | |a Natural language processing | ||
| 653 | |a Image quality | ||
| 653 | |a Inscriptions | ||
| 653 | |a Cultural resources | ||
| 653 | |a Cultural heritage | ||
| 700 | 1 | |a Li, Yujun |u Liaoning Normal University, School of History and Culture, Dalian, China (GRID:grid.440818.1) (ISNI:0000 0000 8664 1765) | |
| 700 | 1 | |a Li, Honglei |u Liaoning Normal University, Digital Protection and Utilisation Laboratory of Historical and Cultural Heritage, Dalian, China (GRID:grid.440818.1) (ISNI:0000 0000 8664 1765) | |
| 773 | 0 | |t Heritage Science |g vol. 13, no. 1 (Dec 2025), p. 326 | |
| 786 | 0 | |d ProQuest |t Materials Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3227339378/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3227339378/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3227339378/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |