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 461–470 of 1209 papers

Title	Date	Tasks	Status
Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices	Sep 14, 2020	Optical Character Recognition (OCR)Quantization	—Unverified
Finding Names in Trove: Named Entity Recognition for Australian Historical Newspapers	Dec 1, 2015	Clusteringnamed-entity-recognition	—Unverified
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering	May 29, 2025	Chart Question AnsweringChart Understanding	—Unverified
Finite State Approach to the Kazakh Nominal Paradigm	Jul 1, 2013	Morphological AnalysisOptical Character Recognition (OCR)	—Unverified
A Proposal of Automatic Error Correction in Text	Sep 24, 2021	Information RetrievalLanguage Modelling	—Unverified
FLELex: a graded lexical resource for French foreign learners	May 1, 2014	Language AcquisitionOptical Character Recognition (OCR)	—Unverified
Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation	Mar 14, 2024	Image to textOptical Character Recognition (OCR)	—Unverified
ChartEye: A Deep Learning Framework for Chart Information Extraction	Aug 28, 2024	Chart UnderstandingClassification	—Unverified
ExTTNet: A Deep Learning Algorithm for Extracting Table Texts from Invoice Images	Feb 3, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Extraction of Line Word Character Segments Directly from Run Length Compressed Printed Text Documents	Mar 30, 2014	Optical Character RecognitionOptical 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