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Trocr Kurrent
An optical character recognition model optimized for 19th-century German handwritten text recognition, fine-tuned based on Microsoft's TrOCR base model
Downloads 384
Release Time : 12/6/2022
Model Overview
This model is specifically designed for recognizing 19th-century German Kurrent script handwritten texts, suitable for historical document digitization and archival processing scenarios
Model Features
Historical Handwriting Optimization
Specially optimized for 19th-century Kurrent script handwriting style
Multi-source Data Training
Incorporates historical document data from archives in Switzerland, Germany, and other countries for training
High Accuracy Recognition
Achieves a low character error rate (CER) of 2.655% on test sets
Model Capabilities
Handwritten text recognition
Historical document digitization
German Kurrent script parsing
Optical character recognition
Use Cases
Historical Archive Digitization
Government Meeting Minutes Transcription
Automatically recognizes handwritten records of 19th-century government meetings
Test set CER 2.655%
Scholar Manuscript Digitization
Processes handwritten lecture notes of scholars like Humboldt
Academic Research Support
Historical Diary Transcription
Automatically recognizes handwritten diaries of historical figures like Eugen Huber
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