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 851–860 of 1209 papers

Title	Date	Tasks	Status
Arabic Character Segmentation Using Projection Based Approach with Profile's Amplitude Filter	Jul 4, 2017	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection	Dec 2, 2024	BinarizationOptical Character Recognition (OCR)	—Unverified
A random forest system combination approach for error detection in digital dictionaries	Oct 30, 2014	Language ModelingLanguage Modelling	—Unverified
Artificial Eye for the Blind	Jul 7, 2023	Objectobject-detection	—Unverified
Artificial neural networks and fuzzy logic for recognizing alphabet characters and mathematical symbols	Jul 6, 2016	Image SegmentationOptical Character Recognition	—Unverified
A Scalable Handwritten Text Recognition System	Apr 19, 2019	Handwriting RecognitionHandwritten Text Recognition	—Unverified
A second-order orientation-contrast stimulus for population-receptive-field-based retinotopic mapping	Jul 10, 2017	Optical Character Recognition (OCR)	—Unverified
A semi-automatic method for document classification in the shipping industry	Mar 29, 2023	ClassificationDocument Classification	—Unverified
A Simple and Practical Approach to Improve Misspellings in OCR Text	Jun 22, 2021	Optical Character Recognition (OCR)	—Unverified
A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning	Aug 15, 2019	Multi-Task LearningOptical 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