Journal of technical research and development

Articles

Vol. 1 No. 3 (2023):

RECOGNITION OFFLINE HANDWRITTEN SIGNATURES BASED ON MACHINE LEARNING

  • Umidjon Akhundjanov
Submitted
November 30, 2023
Published
2023-12-02

Abstract

This article is devoted to the development of a method for detecting forgery of handwritten signatures. The signature is still one of the most common methods of personal identification. Signatures on financial and other documents can be forged, so identifying forgery is an urgent task. This is a binary classification task: determining whether a signature is genuine or fake.

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