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 1071–1080 of 1209 papers

Title	Date	Tasks	Status
Implementation of a Workflow Management System for Non-Expert Users	Dec 1, 2016	ManagementOptical Character Recognition (OCR)	—Unverified
Detection of Text Reuse in French Medical Corpora	Dec 1, 2016	De-identificationOptical Character Recognition (OCR)	—Unverified
Integrating Optical Character Recognition and Machine Translation of Historical Documents	Dec 1, 2016	Language ModelingLanguage Modelling	—Unverified
Align Me: A framework to generate Parallel Corpus Using OCRs and Bilingual Dictionaries	Dec 1, 2016	Active LearningInformation Retrieval	—Unverified
Providing and Analyzing NLP Terms for our Community	Dec 1, 2016	Named Entity Recognition (NER)Optical Character Recognition (OCR)	—Unverified
Statistical Learning for OCR Text Correction	Nov 21, 2016	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Old Content and Modern Tools - Searching Named Entities in a Finnish OCRed Historical Newspaper Collection 1771-1910	Nov 9, 2016	named-entity-recognitionNamed Entity Recognition	—Unverified
Chinese/English mixed Character Segmentation as Semantic Segmentation	Nov 7, 2016	DiversityOptical Character Recognition (OCR)	—Unverified
Latent Tree Language Model	Nov 1, 2016	Automatic Speech Recognition (ASR)Language Modeling	CodeCode Available
Low-resource OCR error detection and correction in French Clinical Texts	Nov 1, 2016	Language ModelingLanguage Modelling	—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 105M	Accuracy (%)	89.6	—	Unverified
2	DTrOCR	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