| Autor: |
Rifki Suwandi, Werman Kasoep, Ramon Luthvi Destria |
| Jazyk: |
English<br />Indonesian |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
JITCE (Journal of Information Technology and Computer Engineering), Vol 7, Iss 01 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2599-1663 |
| Popis: |
In the digital era, preserving old documents to prevent damage is a significant challenge. One solution to this problem is to reconstruct damaged or lost documents using image processing and natural language processing technologies. This article discusses the design of a tool for correcting and reconstructing writing in old papers and documents that can be implemented on a mini PC. The tool uses state-of-the-art algorithms such as Convolutional Neural Network (CNN) for character recognition and Optical Character Recognition (OCR), as well as Image Inpainting and Sequence-to-Sequence (Seq2Seq) algorithms for document reconstruction. Test results show that this tool can recognize characters with high accuracy and reconstruct damaged or lost documents effectively. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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