@inproceedings{7a8998e16e5d4228a9dcb39e368650b0,
title = "Signature analysis system using a convolutional neural network",
abstract = "Identity verification using biometric methods has been used for many years. A special case is a handwritten signature made on a digital device or piece of paper. For the digital analysis and verification of its authenticity, special methods are needed. Unfortunately, this is a rather complicated task that quite often requires complex processing techmques. In this paper, we propose a system of signatures verification consisting of two stages. In the first one, a signature pattern is created. Thanks to this, the first attempt to verify identity takes place. In the case of approval, the second stage is followed by the processing of a graphic sample contaimng a signature by the convolutional neural network. The proposed techmque has been described, tested and discussed due to its practical use.",
author = "Alicja Winnicka and Karolina Kesik and Dawid Polap",
note = "Publisher Copyright: {\textcopyright} 2019 Polish Information Processing Society - as since.; 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019 ; Conference date: 01-09-2019 Through 04-09-2019",
year = "2019",
month = sep,
doi = "10.15439/2019F28",
language = "English",
series = "Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "287--290",
editor = "Maria Ganzha and Leszek Maciaszek and Leszek Maciaszek and Marcin Paprzycki",
booktitle = "Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019",
address = "United States",
}