Papers by Moule Lin
PreP-OCR: A Complete Pipeline for Document Image Restoration and Enhanced OCR Accuracy (2025.acl-long)
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| Challenge: | Existing pipelines that combine document image restoration with semantic-aware post-OCR correction can improve text extraction from degraded images. |
| Approach: | They propose a two-stage pipeline that combines document image restoration with semantic-aware post-OCR correction to enhance both visual clarity and textual consistency. |
| Outcome: | The proposed pipeline reduces character error rates by 63.9-70.3% on 13,831 pages of real historical documents in English, French, and Spanish compared to OCR on raw images. |
Effective Synthetic Data and Test-Time Adaptation for OCR Correction (2024.emnlp-main)
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| Challenge: | Recent research has framed the post-OCR task as a Seq2Seq Neural Machine Translation (NMT) task. |
| Approach: | They propose a method for constructing post-OCR synthetic data with different noise levels using weak supervision. |
| Outcome: | The proposed method reduces CER by 68.67% without relying on manual annotations. |