Vit Base Patch16 224 In21k Writer Identification
Fine-tuned based on Google's ViT model for handwriting recognition tasks
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Release Time : 9/7/2022
Model Overview
This model is a fine-tuned version of Google's ViT (Vision Transformer) base model for handwriting recognition tasks, capable of identifying different authors' handwriting styles.
Model Features
Transformer-based Vision Model
Uses Vision Transformer architecture to process image data with powerful feature extraction capabilities
Handwriting Recognition Capability
Fine-tuned specifically for handwriting recognition tasks, able to distinguish writing styles of different authors
Transfer Learning
Fine-tuned based on a pre-trained ViT model, leveraging the advantages of large-scale image pre-training
Model Capabilities
Handwriting feature extraction
Author identification
Image classification
Use Cases
Document Analysis
Historical Document Author Identification
Identify potential authors of historical documents or manuscripts
Validation set accuracy 42.55%, Top-3 accuracy 68.84%
Handwriting Verification
Verify whether two documents were written by the same author
Security Verification
Signature Verification
Verify the authenticity of signatures
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