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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 531–540 of 1209 papers

Title	Date	Tasks	Status
Improving Document Clustering by Removing Unnatural Language	Sep 1, 2017	ClusteringDocument Layout Analysis	—Unverified
DavarOCR: A Toolbox for OCR and Multi-Modal Document Understanding	Jul 14, 2022	document understandingOptical Character Recognition (OCR)	—Unverified
Automated Error Detection in Digitized Cultural Heritage Documents	Apr 1, 2014	Optical Character Recognition (OCR)Spelling Correction	—Unverified
Data Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection	Feb 25, 2016	Anomaly DetectionOptical Character Recognition	—Unverified
Automated data extraction of bar chart raster images	Nov 9, 2020	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Ancient but Digitized: Developing Handwritten Optical Character Recognition for East Syriac Script Through Creating KHAMIS Dataset	Aug 24, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Improving Handwritten OCR with Training Samples Generated by Glyph Conditional Denoising Diffusion Probabilistic Model	May 31, 2023	DenoisingOptical Character Recognition (OCR)	—Unverified
Improving Long Handwritten Text Line Recognition with Convolutional Multi-way Associative Memory	Nov 5, 2019	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Neural Probabilistic System for Text Recognition	Dec 10, 2018	Optical Character Recognition (OCR)	—Unverified
DanProof: Pedagogical Spell and Grammar Checking for Danish	Sep 1, 2015	Machine TranslationOptical 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