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 461–470 of 1209 papers

Title	Date	Tasks	Status
An End-to-End Khmer Optical Character Recognition using Sequence-to-Sequence with Attention	Jun 21, 2021	DecoderOptical Character Recognition	—Unverified
Finding Names in Trove: Named Entity Recognition for Australian Historical Newspapers	Dec 1, 2015	Clusteringnamed-entity-recognition	—Unverified
An Ensemble of Neural Networks for Non-Linear Segmentation of Overlapped Cursive Script	Apr 7, 2019	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Finite State Approach to the Kazakh Nominal Paradigm	Jul 1, 2013	Morphological AnalysisOptical Character Recognition (OCR)	—Unverified
Chaurah: A Smart Raspberry Pi based Parking System	Dec 28, 2023	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
FLELex: a graded lexical resource for French foreign learners	May 1, 2014	Language AcquisitionOptical Character Recognition (OCR)	—Unverified
Grammatical vs Spelling Error Correction: An Investigation into the Responsiveness of Transformer-based Language Models using BART and MarianMT	Mar 25, 2024	Optical Character Recognition (OCR)speech-recognition	—Unverified
Detection Masking for Improved OCR on Noisy Documents	May 17, 2022	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods	May 31, 2021	ArticlesBIG-bench Machine Learning	—Unverified
D\'etection d'erreurs dans des transcriptions OCR de documents historiques par r\'eseaux de neurones r\'ecurrents multi-niveau (Combining character level and word level RNNs for post-OCR error detection)	May 1, 2018	Optical 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