Work

Signature Verification System Using CNNs

Year: 2025

Type: article

Abstract: In today's digital age, verifying signatures is crucial for authenticating documents and preventing forgery. Traditional methods rely on manual inspection, which can be time: consuming and prone to errors. To address this, researchers have developed signature verification systems using Convolutional Neural Networks (CNNs). These systems leverage machine learning to automatically distinguish between genuine and forged signatures, enhancing accuracy and efficiency.

Source: International Journal of Advanced Research in Science Communication and Technology

DOI: 10.48175/ijarsct-23771

Authors: Mr. Omkar V. Khute, Ms. Leena Patil, Mr. Yash Chaudhari, Mr. Dhiraj Patole, Mr. Sarthak Nikam

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4408527581

FWCI:

Cites: 1

Cited by:

Related to: 10