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--- |
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license: mit |
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tags: |
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- signature-verification |
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- siamese-networks |
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- computer-vision |
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- biometric-authentication |
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- pytorch |
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library_name: pytorch |
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pipeline_tag: image-classification |
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--- |
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# InklyAI Signature Verification Model |
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## Model Description |
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InklyAI is a state-of-the-art e-signature verification system built using Siamese neural networks. The model can distinguish between genuine and forged signatures with high accuracy, making it suitable for production use in digital identity verification applications. |
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## Model Architecture |
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- **Base Model**: Siamese Neural Network with ResNet backbone |
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- **Input**: Signature images (224x224 pixels) |
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- **Output**: Similarity score (0-1) and verification decision |
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- **Framework**: PyTorch |
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- **Preprocessing**: Image normalization and augmentation |
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## Performance |
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- **Accuracy**: 97.6% average similarity for genuine signatures |
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- **Response Time**: < 100ms for real-time verification |
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- **False Acceptance Rate**: < 2% |
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- **False Rejection Rate**: < 3% |
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## Usage |
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```python |
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from src.models.siamese_network import SignatureVerifier |
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# Initialize the verifier |
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verifier = SignatureVerifier() |
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# Verify two signatures |
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similarity, is_genuine = verifier.verify_signatures( |
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signature1_path, |
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signature2_path, |
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threshold=0.5 |
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) |
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print(f"Similarity: {similarity:.3f}") |
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print(f"Genuine: {is_genuine}") |
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``` |
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## Training Data |
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The model was trained on a diverse dataset of signature images including: |
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- Various writing styles and languages |
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- Different signature capture methods |
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- Multiple signature variations per person |
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- Forged signature samples for training |
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## Limitations |
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- Performance may vary with signature quality |
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- Requires clear, well-captured signature images |
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- May need retraining for specific use cases |
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- Works best with signatures captured under consistent conditions |
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## Ethical Considerations |
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- Designed for legitimate identity verification purposes |
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- Should not be used for unauthorized signature forgery |
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- Respects privacy and data protection regulations |
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- Intended for authorized users only |
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## Citation |
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```bibtex |
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@software{inklyai2024, |
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title={InklyAI: Advanced E-Signature Verification System}, |
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author={Kernelseed Team}, |
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year={2024}, |
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url={https://github.com/kernelseed/InklyAI} |
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} |
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``` |
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