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 421–430 of 1209 papers

Title	Date	Tasks	Status
Enhancement of Bengali OCR by Specialized Models and Advanced Techniques for Diverse Document Types	Feb 7, 2024	Optical Character Recognition (OCR)Table Recognition	—Unverified
Enhancement of text recognition for hanja handwritten documents of Ancient Korea	Dec 14, 2024	Data Augmentationobject-detection	—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
From Training-Free to Adaptive: Empirical Insights into MLLMs' Understanding of Detection Information	Jan 31, 2024	Hallucinationobject-detection	—Unverified
Enhancing OCR Performance through Post-OCR Models: Adopting Glyph Embedding for Improved Correction	Aug 29, 2023	Optical Character Recognition (OCR)	—Unverified
Enhancing Question Answering on Charts Through Effective Pre-training Tasks	Jun 14, 2024	document understandingOptical Character Recognition (OCR)	—Unverified
Enhancing Vehicle Entrance and Parking Management: Deep Learning Solutions for Efficiency and Security	Dec 5, 2023	Face DetectionLicense Plate Recognition	—Unverified
Entropy Heat-Mapping: Localizing GPT-Based OCR Errors with Sliding-Window Shannon Analysis	Apr 30, 2025	Optical 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

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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