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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 551–600 of 1209 papers

TitleStatusHype
A Masked Bounding-Box Selection Based ResNet Predictor for Text Rotation Prediction—0
You’ve translated it, now what?—0
A Black-Box Attack on Optical Character Recognition Systems—0
An Energy Activity Dataset for Smart Homes—0
AiM: Taking Answers in Mind to Correct Chinese Cloze Tests in Educational ApplicationsCode0
Effectiveness of Mining Audio and Text Pairs from Public Data for Improving ASR Systems for Low-Resource Languages—0
Visual Subtitle Feature Enhanced Video Outline Generation—0
Graph Neural Networks and Representation Embedding for Table Extraction in PDF DocumentsCode1
An End-to-End OCR Framework for Robust Arabic-Handwriting Recognition using a Novel Transformers-based Model and an Innovative 270 Million-Words Multi-Font Corpus of Classical Arabic with Diacritics—0
To show or not to show: Redacting sensitive text from videos of electronic displays—0
Character decomposition to resolve class imbalance problem in Hangul OCRCode0
Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features—0
Optimal Boxes: Boosting End-to-End Scene Text Recognition by Adjusting Annotated Bounding Boxes via Reinforcement Learning—0
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression RecognitionCode2
Marior: Margin Removal and Iterative Content Rectification for Document Dewarping in the WildCode1
You Actually Look Twice At it (YALTAi): using an object detection approach instead of region segmentation within the Kraken engineCode1
Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting—0
DEXTER: An end-to-end system to extract table contents from electronic medical health documents—0
DavarOCR: A Toolbox for OCR and Multi-Modal Document Understanding—0
GMN: Generative Multi-modal Network for Practical Document Information Extraction—0
Towards Multimodal Vision-Language Models Generating Non-Generic Text—0
Detection of Furigana Text in ImagesCode1
BusiNet -- a Light and Fast Text Detection Network for Business Documents—0
Sequence-aware multimodal page classification of Brazilian legal documentsCode0
Challenging America: Modeling language in longer time scales—0
Multistep Automated Data Labelling Procedure (MADLaP) for Thyroid Nodules on Ultrasound: An Artificial Intelligence Approach for Automating Image Annotation—0
iExam: A Novel Online Exam Monitoring and Analysis System Based on Face Detection and RecognitionCode0
Towards Optimizing OCR for Accessibility—0
Broken News: Making Newspapers Accessible to Print-Impaired—0
RDU: A Region-based Approach to Form-style Document Understanding—0
An Evaluation of OCR on Egocentric DataCode0
Transformer based Urdu Handwritten Text Optical Character Reader—0
PP-OCRv3: More Attempts for the Improvement of Ultra Lightweight OCR System—0
Contrastive Graph Multimodal Model for Text Classification in Videos—0
Two Decades of Bengali Handwritten Digit Recognition: A Survey—0
Introducing One Sided Margin Loss for Solving Classification Problems in Deep Networks—0
Generating Monolingual Dataset for Low Resource Language Bodo from old books using Google Keep—0
A Language Modelling Approach to Quality Assessment of OCR’ed Historical Text—0
An Open Source Contractual Language Understanding Application Using Machine LearningCode0
Multilingual Named Entity Recognition for Medieval Charters Using Stacked Embeddings and Bert-based Models.—0
Handwritten Character Generation using Y-Autoencoder for Character Recognition Model Training—0
CAMIO: A Corpus for OCR in Multiple Languages—0
Between History and Natural Language Processing: Study, Enrichment and Online Publication of French Parliamentary Debates of the Early Third Republic (1881-1899)—0
Simulation d’erreurs d’OCR dans les systèmes de TAL pour le traitement de données anachroniques (Simulation of OCR errors in NLP systems for processing anachronistic data)—0
Toolbox : une chaîne de traitement de corpus pour les humanités numériques (Toolbox : a corpus processing pipeline for digital humanities)—0
Reconnaissance d’entités nommées sur des sorties OCR bruitées : des pistes pour la désambiguïsation morphologique automatique (Resolution of entity linking issues on noisy OCR output : automatic disambiguation tracks)—0
MaskOCR: Text Recognition with Masked Encoder-Decoder Pretraining—0
Delivering Document Conversion as a Cloud Service with High Throughput and ResponsivenessCode2
Optical character recognition quality affects perceived usefulness of historical newspaper clippings—0
hmBERT: Historical Multilingual Language Models for Named Entity RecognitionCode1
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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