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 911–920 of 1209 papers

Title	Date	Tasks	Status
Object Detection and Recognition of Swap-Bodies using Camera mounted on a Vehicle	Apr 17, 2020	Data Augmentationobject-detection	—Unverified
OCR4all -- An Open-Source Tool Providing a (Semi-)Automatic OCR Workflow for Historical Printings	Sep 9, 2019	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
OCR accuracy improvement on document images through a novel pre-processing approach	Sep 11, 2015	BinarizationOptical Character Recognition	—Unverified
OCR and Automated Translation for the Navigation of non-English Handsets: A Feasibility Study with Arabic	Nov 1, 2014	Machine TranslationOptical Character Recognition (OCR)	—Unverified
OCR and post-correction of historical Finnish texts	May 1, 2017	Optical Character Recognition (OCR)Spelling Correction	—Unverified
OCRAPOSE II: An OCR-based indoor positioning system using mobile phone images	Apr 19, 2017	Depth EstimationOptical Character Recognition	—Unverified
OCR++: A Robust Framework For Information Extraction from Scholarly Articles	Sep 23, 2016	ArticlesOptical Character Recognition (OCR)	—Unverified
OCR, Classification & Machine Translation (OCCAM)	Nov 1, 2020	Classificationimage-classification	—Unverified
OCR Error Correction Using Character Correction and Feature-Based Word Classification	Apr 21, 2016	General ClassificationLanguage Modeling	—Unverified
OCR evaluation tools for the 21st century	Feb 1, 2019	Optical Character Recognition (OCR)	—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