Omar Tarek has presented his paper entitled ‘Forensic Handwritten Signature Identification Using Deep Learning” which proposed a system that focuses on the identification and detection of handwritten signature forgeries. The paper suggested how the proposed system uses contemporary methods that utilize a deep learning approach for image classification to help forensic examiners reliably authenticate and measure the genuineness of handwritten signatures inside documents.
The paper is now published, and can be viewed here: