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 1051–1100 of 1209 papers

TitleStatusHype
OCRAPOSE II: An OCR-based indoor positioning system using mobile phone images—0
EAST: An Efficient and Accurate Scene Text DetectorCode1
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
Case Study of a highly automated Layout Analysis and OCR of an incunabulum: 'Der Heiligen Leben' (1488)Code0
LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed BooksCode0
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
Providing and Analyzing NLP Terms for our Community—0
Detection of Text Reuse in French Medical Corpora—0
Integrating Optical Character Recognition and Machine Translation of Historical Documents—0
Implementation of a Workflow Management System for Non-Expert Users—0
Align Me: A framework to generate Parallel Corpus Using OCRs and Bilingual Dictionaries—0
Statistical Learning for OCR Text Correction—0
Old Content and Modern Tools - Searching Named Entities in a Finnish OCRed Historical Newspaper Collection 1771-1910—0
Chinese/English mixed Character Segmentation as Semantic Segmentation—0
Low-resource OCR error detection and correction in French Clinical Texts—0
Latent Tree Language ModelCode0
Still not there? Comparing Traditional Sequence-to-Sequence Models to Encoder-Decoder Neural Networks on Monotone String Translation Tasks—0
Proposal for Automatic License and Number Plate Recognition System for Vehicle Identification—0
OCR++: A Robust Framework For Information Extraction from Scholarly Articles—0
Star-net: A spatial attention residue network for scene text recognition.—0
Image-to-Markup Generation with Coarse-to-Fine AttentionCode3
OCR of historical printings with an application to building diachronic corpora: A case study using the RIDGES herbal corpus—0
Pynini: A Python library for weighted finite-state grammar compilation—0
Combining Phonology and Morphology for the Normalization of Historical Texts—0
Data-Driven Spelling Correction using Weighted Finite-State MethodsCode0
Semi-automated annotation of page-based documents within the Genre and Multimodality framework—0
Evaluating Inter-Annotator Agreement on Historical Spelling Normalization—0
Unsupervised morph segmentation and statistical language models for vocabulary expansion—0
N-gram language models for massively parallel devices—0
Benchmark for License Plate Character Segmentation—0
Artificial neural networks and fuzzy logic for recognizing alphabet characters and mathematical symbols—0
How many faces can be recognized? Performance extrapolation for multi-class classification—0
An Unsupervised Model of Orthographic Variation for Historical Document TranscriptionCode0
An efficient way for segmentation of Bangla characters in printed document using curved scanningCode0
A Generic Method for Automatic Ground Truth Generation of Camera-captured Documents—0
Extracting Weighted Language Lexicons from Wikipedia—0
1 Million Captioned Dutch Newspaper Images—0
Using SMT for OCR Error Correction of Historical Texts—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