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 876–900 of 1209 papers

TitleStatusHype
Automated Quality Control System for Canned Tuna Production using Artificial Vision—0
Automated Transcription of Non-Latin Script Periodicals: A Case Study in the Ottoman Turkish Print Archive—0
Automated Translation of a Literary Work: A Pilot Study—0
Automatic Classification of Pathology Reports using TF-IDF Features—0
Automatic Compositor Attribution in the First Folio of Shakespeare—0
Auto-ML Deep Learning for Rashi Scripts OCR—0
Balanced Korean Word Spacing with Structural SVM—0
Bambara and Maninka Manding Languages Written Corpora Project (``Projet des corpus \'ecrits des langues manding : le bambara, le maninka'') [in French]—0
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods—0
Bangla Text Recognition from Video Sequence: A New Focus—0
BART for Post-Correction of OCR Newspaper Text—0
@Bench: Benchmarking Vision-Language Models for Human-centered Assistive Technology—0
Benchmark for License Plate Character Segmentation—0
Benchmarking Algorithms for Automatic License Plate Recognition—0
Bengali Document Layout Analysis -- A YOLOV8 Based Ensembling Approach—0
Bengali Document Layout Analysis with Detectron2—0
Bengali Handwritten Digit Recognition using CNN with Explainable AI—0
BennettNLP at SemEval-2020 Task 8: Multimodal sentiment classification Using Hybrid Hierarchical Classifier—0
Between History and Natural Language Processing: Study, Enrichment and Online Publication of French Parliamentary Debates of the Early Third Republic (1881-1899)—0
Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMs—0
Beyond the Mud: Datasets and Benchmarks for Computer Vision in Off-Road Racing—0
Bidirectional Trained Tree-Structured Decoder for Handwritten Mathematical Expression Recognition—0
BIOfid Dataset: Publishing a German Gold Standard for Named Entity Recognition in Historical Biodiversity Literature—0
BLPnet: A new DNN model and Bengali OCR engine for Automatic License Plate Recognition—0
Modelling Lips-State Detection Using CNN for Non-Verbal Communications—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