A Survey Paper of a Noval Approach for Fake signature Verification and Detection Technique Using Deep Learning Method
Abstract
— Detecting signature forgeries is an important task with applications spanning from forensic investigations to banking security. Deep learning methods have shown great promise in recent years for automating and enhancing the precision of bogus signature detection systems. This survey study offers a thorough summary of the most recent deep learning techniques used in the field of signature forgery detection. For this assignment, we do a thorough examination and analysis of a large number of research articles covering a variety of topics, including network topologies, datasets, evaluation measures, and difficulties faced when deploying deep learning models. We also presented a method to detect the fake signature using Convolutional neural Networks (CNN). We hope that this review will give scholars, industry professionals, and interested parties a thorough grasp of the state of the art, obstacles to overcome, and potential paths forward in the use of deep learning to false signature detection.!
Keywords
Forged Signature, Convolutional Neural Networks (CNN), Digital Transactions, Signature Authentication