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 1081–1090 of 1209 papers

Title	Date	Tasks	Status
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
Proposal for Automatic License and Number Plate Recognition System for Vehicle Identification	Oct 9, 2016	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
OCR++: A Robust Framework For Information Extraction from Scholarly Articles	Sep 23, 2016	ArticlesOptical Character Recognition (OCR)	—Unverified
Star-net: A spatial attention residue network for scene text recognition.	Sep 20, 2016	Optical Character Recognition (OCR)Scene Text Recognition	—Unverified
OCR of historical printings with an application to building diachronic corpora: A case study using the RIDGES herbal corpus	Aug 6, 2016	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Combining Phonology and Morphology for the Normalization of Historical Texts	Aug 1, 2016	Machine TranslationOptical Character Recognition (OCR)	—Unverified
N-gram language models for massively parallel devices	Aug 1, 2016	Language ModelingLanguage Modelling	—Unverified
Data-Driven Spelling Correction using Weighted Finite-State Methods	Aug 1, 2016	Optical Character Recognition (OCR)Spelling Correction	CodeCode Available
Pynini: A Python library for weighted finite-state grammar compilation	Aug 1, 2016	Automatic Speech Recognition (ASR)Optical Character Recognition (OCR)	—Unverified
Evaluating Inter-Annotator Agreement on Historical Spelling Normalization	Aug 1, 2016	Optical Character Recognition (OCR)Part-Of-Speech Tagging	—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