Handwritten Signature Identification

• Tech Stack: Python, Convolutional Neural Networks (CNN), Data Preprocessing, Machine Learning, TensorFlow, Pandas

CNN-Based Signature Verification: Developed a Convolutional Neural Network model to distinguish between real and forged signatures, achieving over 95.2% accuracy

Advanced Preprocessing & Data Augmentation: Applied image preprocessing and augmentation techniques to improve model robustness against varied writing styles and signature variations

Transfer Learning for Generalization: Leveraged transfer learning to enhance model performance and generalization on unseen signature samples, ensuring effective real-world verification

Robust Fraud Detection: Successfully designed a system capable of detecting fraudulent signatures with high reliability, demonstrating practical applicability in security and authentication tasks