| 英文摘要 |
The introduction of new technologies requires long-term evaluation and planning. Artificial intelligence, a rising star in the information sector, is gaining prominence. In the museum field, AI is being explored for its potential in exhibitions, marketing, and even collections management to create new experiences and improve operational efficiency. The National Museum of Taiwan Literature primarily houses manuscripts, letters, and books, and has long been committed to inspecting the deterioration of its collections and establishing data records, achieving significant results. However, given the vast number of collections, the process of inspecting and grading items is time-consuming. By introducing AI visual analysis technology to assess and assist in evaluating the deterioration of collections, the museum can accurately monitor the condition of its collections and enhance inspection efficiency.
Currently, in the field of professional preservation of paper-based and book collections, both domestically and internationally, there are very few databases related to collection deterioration or the use of AI imaging technology. This research focuses on collecting images of deteriorated conditions and preparing AI training data, investing in AI learning, training, and validation. The goal is to provide museums with AI-based automated recognition for diagnosing collection deterioration, replacing manual labor, and integrating this technology into the collection inspection and logging process. This approach will effectively enhance collection management operations and allow for a more comprehensive understanding of the entire collection. |
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