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Large Language Models for Simultaneous Named Entity Extraction and Spelling Correction
Language Models (LMs) such as BERT, have been shown to perform well on the task of identifying Named Entities (NE) in text.
Automatic Detection and Rectification of Paper Receipts on Smartphones
We show that our proposed method robustly detects the four corners of a receipt, giving a receipt detection accuracy of 85. 3% on real-world data, compared to only 36. 9% with a traditional edge detection-based approach.
Extending TrOCR for Text Localization-Free OCR of Full-Page Scanned Receipt Images
To this end, we propose a localization-free document-level OCR model for transcribing all the characters in a receipt image into an ordered sequence end-to-end.
Optical Character Recognition
Optical Character Recognition (OCR)
