Optical Character Recognition (OCR)

Optical Character Recognition or Optical Character Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo, license plates in cars...) or from subtitle text superimposed on an image (for example: from a television broadcast)

Papers

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Showing 541–550 of 1209 papers

Title	Date	Tasks	Status
CryptoDL: Deep Neural Networks over Encrypted Data	Nov 14, 2017	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Autocorrection of arabic common errors for large text corpus	Oct 1, 2014	Morphological AnalysisOptical Character Recognition (OCR)	—Unverified
Improving OCR Quality in 19th Century Historical Documents Using a Combined Machine Learning Based Approach	Jan 15, 2024	Optical Character Recognition (OCR)	—Unverified
Crowdsourcing an OCR Gold Standard for a German and French Heritage Corpus	May 1, 2016	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Advanced Knowledge Extraction of Physical Design Drawings, Translation and conversion to CAD formats using Deep Learning	Mar 17, 2024	Edge DetectionLine Detection	—Unverified
CREPE: Coordinate-Aware End-to-End Document Parser	May 1, 2024	document understandingOptical Character Recognition (OCR)	—Unverified
Improving OCR-Based Image Captioning by Incorporating Geometrical Relationship	Jun 19, 2021	Image CaptioningOptical Character Recognition (OCR)	—Unverified
Improving Optical Character Recognition of Finnish Historical Newspapers with a Combination of Fraktur \& Antiqua Models and Image Preprocessing	May 1, 2017	Boundary DetectionInformation Retrieval	—Unverified
Corrupted but Not Broken: Understanding and Mitigating the Negative Impacts of Corrupted Data in Visual Instruction Tuning	Feb 18, 2025	Optical Character Recognition (OCR)	—Unverified
Correction of OCR Word Segmentation Errors in Articles from the ACL Collection through Neural Machine Translation Methods	May 1, 2018	ArticlesGrammatical Error Correction	—Unverified

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All datasets Benchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical Study VideoDB's OCR Benchmark Public Collection FSNS - Test I2L-140K SUT im2latex-100k

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DTrOCR	Accuracy (%)	89.6	—	Unverified
2	DTrOCR 105M	Accuracy (%)	89.6	—	Unverified
3	MaskOCR-L	Accuracy (%)	82.6	—	Unverified
4	TransOCR	Accuracy (%)	72.8	—	Unverified
5	SRN	Accuracy (%)	65	—	Unverified
6	MORAN	Accuracy (%)	64.3	—	Unverified
7	SEED	Accuracy (%)	61.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GPT-4o	Average Accuracy	76.22	—	Unverified
2	Gemini-1.5 Pro	Average Accuracy	76.13	—	Unverified
3	Claude-3 Sonnet	Average Accuracy	67.71	—	Unverified
4	RapidOCR	Average Accuracy	56.98	—	Unverified
5	EasyOCR	Average Accuracy	49.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STREET	Sequence error	27.54	—	Unverified
2	SEE	Sequence error	22	—	Unverified
3	AttentionOCR_Inception-resnet-v2_Location	Sequence error	15.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	I2L-NOPOOL	BLEU	89.09	—	Unverified
2	I2L-STRIPS	BLEU	89	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Tesseract	Character Error Rate (CER)	0.08	—	Unverified
2	EasyOCR	Character Error Rate (CER)	0.07	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	I2L-STRIPS	BLEU	88.86	—	Unverified