Exploiting Script Similarities to Compensate for the Large Amount of Data in Training Tesseract LSTM: Towards Kurdish OCR
Applications based on Long-Short-Term Memory (LSTM) require large amounts of data for their training. Tesseract LSTM is a popular Optical Character Recognition (OCR) engine that has been trained and used in various languages. However, its training becomes obstructed when the target language is not r...
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| Автори: | , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
MDPI AG
2021-10-01
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| Серія: | Applied Sciences |
| Предмети: | |
| Онлайн доступ: | https://www.mdpi.com/2076-3417/11/20/9752 |
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