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 1131–1140 of 1209 papers

Title	Date	Tasks	Status
Identifying OCRs in cfDNA WGS Data by Correlation Clustering	Feb 19, 2022	Clusteringgraph construction	—Unverified
Image-based Natural Language Understanding Using 2D Convolutional Neural Networks	Oct 24, 2018	ClassificationGeneral Classification	—Unverified
Image preprocessing and modified adaptive thresholding for improving OCR	Nov 28, 2021	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Image Processing Based Scene-Text Detection and Recognition with Tesseract	Apr 17, 2020	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Implementation of a Workflow Management System for Non-Expert Users	Dec 1, 2016	ManagementOptical Character Recognition (OCR)	—Unverified
Important New Developments in Arabographic Optical Character Recognition (OCR)	Mar 28, 2017	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Improve CAPTCHA's Security Using Gaussian Blur Filter	Oct 16, 2014	Optical Character Recognition (OCR)	—Unverified
Improved Typesetting Models for Historical OCR	Jun 1, 2014	Optical Character Recognition (OCR)	—Unverified
Improvement in Semantic Address Matching using Natural Language Processing	Apr 17, 2024	Optical Character Recognition (OCR)	—Unverified
Improve Sentence Alignment by Divide-and-conquer	Jan 18, 2022	Optical Character Recognition (OCR)Sentence	—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