In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …

The offline signatures are the most widely adopted biometric authentication techniques in
banking systems, administrative and financial applications due to its simplicity and …

Due to the rapid growth in artificial intelligence (AI) and deep learning (DL) approaches, the
security and robustness of the deployed algorithms need to be guaranteed. The security …

Automated bank cheque verification using image processing is an attempt to complement
the present cheque truncation system, as well as to provide an alternate methodology for the …

Handwritten signature is a common biometric trait, widely used for confirming the presence
or the consent of a person. Offline Signature Verification (OSV) is the task of verifying the …

Dynamic time war** (DTW) is a popular technique for sequence alignment, and is the de
facto standard for dynamic signature verification. In this paper, we go a significant step …

Biometric systems are playing a key role in the multitude of applications and placed at the
center of debate in the scientific research community. Among the numerous biometric …

Convolutional Neural Networks (CNNs) models are one of the most frequently used deep
learning networks, and extensively used in both academia and industry. Recent studies …

In this paper, we tackle the challenge of white-box false positive adversarial attacks on
contrastive loss based offline handwritten signature verification models. We propose a novel …

Machine learning algorithms have had a profound impact on the field of computer science
over the past few decades. The performance of these algorithms heavily depends on the …