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 991–1000 of 1209 papers

Title	Date	Tasks	Status
Towards Processing of the Oral History Interviews and Related Printed Documents	May 1, 2018	Automatic Speech Recognition (ASR)Optical Character Recognition (OCR)	—Unverified
Building A Handwritten Cuneiform Character Imageset	May 1, 2018	Machine TranslationOptical Character Recognition (OCR)	—Unverified
PDFAnno: a Web-based Linguistic Annotation Tool for PDF Documents	May 1, 2018	Coreference ResolutionOptical Character Recognition (OCR)	CodeCode Available
Delta vs. N-Gram Tracing: Evaluating the Robustness of Authorship Attribution Methods	May 1, 2018	Authorship AttributionOptical Character Recognition (OCR)	—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
Computer-assisted Speaker Diarization: How to Evaluate Human Corrections	May 1, 2018	Active LearningFace Recognition	—Unverified
Measuring Innovation in Speech and Language Processing Publications.	May 1, 2018	Information RetrievalOptical Character Recognition (OCR)	—Unverified
Matics Software Suite: New Tools for Evaluation and Data Exploration	May 1, 2018	Optical Character Recognition (OCR)Speaker Diarization	—Unverified
Low-resource Post Processing of Noisy OCR Output for Historical Corpus Digitisation	May 1, 2018	Optical Character Recognition (OCR)	—Unverified
Correction of OCR Word Segmentation Errors in Articles from the ACL Collection through Neural Machine Translation Methods	May 1, 2018	ArticlesGrammatical Error Correction	—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 105M	Accuracy (%)	89.6	—	Unverified
2	DTrOCR	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