SOTAVerified

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 1051–1075 of 1209 papers

TitleStatusHype
A System for Identifying and Exploring Text Repetition in Large Historical Document Corpora—0
Automatic Compositor Attribution in the First Folio of Shakespeare—0
Scatteract: Automated extraction of data from scatter plots—0
OCRAPOSE II: An OCR-based indoor positioning system using mobile phone images—0
Attention-based Extraction of Structured Information from Street View ImageryCode0
Effective search space reduction for spell correction using character neural embeddings—0
Important New Developments in Arabographic Optical Character Recognition (OCR)—0
Content-based similar document image retrieval using fusion of CNN features—0
A Holistic Approach for Optimizing DSP Block Utilization of a CNN implementation on FPGA—0
Twitter100k: A Real-world Dataset for Weakly Supervised Cross-Media Retrieval—0
Endangered Data for Endangered Languages: Digitizing Print dictionaries—0
End-to-End Interpretation of the French Street Name Signs DatasetCode0
Language Independent Single Document Image Super-Resolution using CNN for improved recognition—0
Document Decomposition of Bangla Printed Text—0
LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed BooksCode0
Case Study of a highly automated Layout Analysis and OCR of an incunabulum: 'Der Heiligen Leben' (1488)Code0
Profiling of OCR'ed Historical Texts Revisited—0
Mining Spatio-temporal Data on Industrialization from Historical RegistriesCode0
Recognition of Text Image Using Multilayer Perceptron—0
papago: A Machine Translation Service with Word Sense Disambiguation and Currency Conversion—0
Implementation of a Workflow Management System for Non-Expert Users—0
Detection of Text Reuse in French Medical Corpora—0
Integrating Optical Character Recognition and Machine Translation of Historical Documents—0
Align Me: A framework to generate Parallel Corpus Using OCRs and Bilingual Dictionaries—0
Providing and Analyzing NLP Terms for our Community—0
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All datasetsBenchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical StudyVideoDB's OCR Benchmark Public CollectionFSNS - TestI2L-140KSUTim2latex-100k

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DTrOCRAccuracy (%)89.6—Unverified
2DTrOCR 105MAccuracy (%)89.6—Unverified
3MaskOCR-LAccuracy (%)82.6—Unverified
4TransOCRAccuracy (%)72.8—Unverified
5SRNAccuracy (%)65—Unverified
6MORANAccuracy (%)64.3—Unverified
7SEEDAccuracy (%)61.2—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4oAverage Accuracy76.22—Unverified
2Gemini-1.5 ProAverage Accuracy76.13—Unverified
3Claude-3 SonnetAverage Accuracy67.71—Unverified
4RapidOCRAverage Accuracy56.98—Unverified
5EasyOCRAverage Accuracy49.3—Unverified
#ModelMetricClaimedVerifiedStatus
1STREETSequence error27.54—Unverified
2SEESequence error22—Unverified
3AttentionOCR_Inception-resnet-v2_LocationSequence error15.8—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-NOPOOLBLEU89.09—Unverified
2I2L-STRIPSBLEU89—Unverified
#ModelMetricClaimedVerifiedStatus
1TesseractCharacter Error Rate (CER)0.08—Unverified
2EasyOCRCharacter Error Rate (CER)0.07—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-STRIPSBLEU88.86—Unverified