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 641–650 of 1209 papers

Title	Date	Tasks	Status
Machine Learning Construction: implications to cybersecurity	Jun 24, 2019	BIG-bench Machine LearningOptical Character Recognition	—Unverified
Statistical Machine Translation Improvement based on Phrase Selection	Sep 1, 2015	Language ModellingMachine Translation	—Unverified
Still not there? Comparing Traditional Sequence-to-Sequence Models to Encoder-Decoder Neural Networks on Monotone String Translation Tasks	Oct 25, 2016	DecoderGrapheme-to-Phoneme Conversion	—Unverified
STRIDE : Scene Text Recognition In-Device	May 17, 2021	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Structured Analysis and Comparison of Alphabets in Historical Handwritten Ciphers	Oct 29, 2024	CryptanalysisOptical Character Recognition (OCR)	—Unverified
Sum-Product Networks for Sequence Labeling	Jul 6, 2018	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
SuperOCR: A Conversion from Optical Character Recognition to Image Captioning	Nov 21, 2020	Image CaptioningLicense Plate Recognition	—Unverified
SuperOCR for ALTA 2017 Shared Task	Dec 1, 2017	Language ModelingLanguage Modelling	—Unverified
Survey of Computational Approaches to Lexical Semantic Change	Nov 15, 2018	Change DetectionInformation Retrieval	—Unverified
SVDocNet: Spatially Variant U-Net for Blind Document Deblurring	Sep 14, 2019	DeblurringOptical Character Recognition	—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