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 851–900 of 1209 papers

TitleStatusHype
A Hybrid Swarm and Gravitation based feature selection algorithm for Handwritten Indic Script Classification problem—0
Development of a New Image-to-text Conversion System for Pashto, Farsi and Traditional Chinese—0
A Gaussian Process Upsampling Model for Improvements in Optical Character RecognitionCode0
OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation—0
How Much Data Do You Need? About the Creation of a Ground Truth for Black Letter and the Effectiveness of Neural OCR—0
Books of Hours. the First Liturgical Data Set for Text Segmentation.—0
Preserving Semantic Information from Old Dictionaries: Linking Senses of the `Altfranz\"osisches W\"orterbuch' to WordNet—0
Constructing a Public Meeting Corpus—0
Time-Aware Word Embeddings for Three Lebanese News ArchivesCode0
Building OCR/NER Test Collections—0
MatriVasha: A Multipurpose Comprehensive Database for Bangla Handwritten Compound Characters—0
A Skip-connected Multi-column Network for Isolated Handwritten Bangla Character and Digit recognitionCode0
A Tool for Facilitating OCR Postediting in Historical DocumentsCode0
Image Processing Based Scene-Text Detection and Recognition with Tesseract—0
Object Detection and Recognition of Swap-Bodies using Camera mounted on a Vehicle—0
An Evaluation of DNN Architectures for Page Segmentation of Historical NewspapersCode0
Sparse Concept Coded Tetrolet Transform for Unconstrained Odia Character Recognition—0
Towards Accurate Scene Text Recognition with Semantic Reasoning Networks—0
Real-time information retrieval from Identity cards—0
TextCaps: a Dataset for Image Captioning with Reading Comprehension—0
Confronting the Constraints for Optical Character Segmentation from Printed Bangla Text Image—0
Multistage Curvilinear Coordinate Transform Based Document Image Dewarping using a Novel Quality Estimator—0
Investigating the Decoders of Maximum Likelihood Sequence Models: A Look-ahead Approach—0
ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep LearningCode0
Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks—0
Plague Dot Text: Text mining and annotation of outbreak reports of the Third Plague Pandemic (1894-1952)—0
Pseudo-Bidirectional Decoding for Local Sequence Transduction—0
Table Structure Extraction with Bi-directional Gated Recurrent Unit Networks—0
Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)—0
DDI-100: Dataset for Text Detection and RecognitionCode0
Evaluating Usage of Images for App Classification—0
Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic ManuscriptsCode0
Visual Summarization of Scholarly Videos using Word Embeddings and Keyphrase Extraction—0
Cascaded Detail-Preserving Networks for Super-Resolution of Document Images—0
Handwritten and Machine printed OCR for Geez Numbers Using Artificial Neural Network—0
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction—0
Vehicle-Rear: A New Dataset to Explore Feature Fusion for Vehicle Identification Using Convolutional Neural NetworksCode0
Recognition of Images of Korean Characters Using Embedded Networks—0
Improving Long Handwritten Text Line Recognition with Convolutional Multi-way Associative Memory—0
VASTA: A Vision and Language-assisted Smartphone Task Automation System—0
BIOfid Dataset: Publishing a German Gold Standard for Named Entity Recognition in Historical Biodiversity Literature—0
DeepErase: Weakly Supervised Ink Artifact Removal in Document Text ImagesCode0
From the Paft to the Fiiture: a Fully Automatic NMT and Word Embeddings Method for OCR Post-CorrectionCode0
Rosetta: Large scale system for text detection and recognition in images—0
Membership Model Inversion Attacks for Deep Networks—0
MIDV-2019: Challenges of the modern mobile-based document OCRCode0
Parallel Iterative Edit Models for Local Sequence TransductionCode0
NASS-AI: Towards Digitization of Parliamentary Bills using Document Level Embedding and Bidirectional Long Short-Term MemoryCode0
DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression NetworksCode0
Multi-modal Page Stream Segmentation with Convolutional Neural NetworksCode0
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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