Deep Learning Methods for Signature Verification
JULURI SAMATHA, Madhavi Gudavalli · 2023
In the contemporary digital landscape, individuals are increasingly utilizing online services with remarkable ease. Deep learning technology has become indispensable in applications where precision and efficiency are paramount. Among these, handwritten signature verification is a pivotal application demanding exceptional accuracy. This paper compares different deep-learning techniques applied to signature verification to ascertain an individual's authorization status. We explore various methodologies, including CNN, LSTM, Google Net, and Mobile Net, to discern the authenticity of the signature and confirm the individual's identity. Our proposed method demonstrates promising results in improving the security of digital transactions and identity verification processes.