Metric meta-learning and intrinsic Riemannian embedding for writer independent offline signature verification
A Giazitzis, EN Zois - Expert Systems with Applications, 2025 - Elsevier
Offline signature verification necessitates the involvement of machine learning visual
recognition techniques. Efficient signature e-verifiers in machine learning and data analysis …
recognition techniques. Efficient signature e-verifiers in machine learning and data analysis …
SigmML: Metric meta-learning for Writer Independent Offline Signature Verification in the Space of SPD Matrices
A Giazitzis, EN Zois - Proceedings of the IEEE/CVF Winter …, 2024 - openaccess.thecvf.com
The handwritten signature has been identified as one of the most popular biometric means
of human consent and/or presence for transactions held by any number of physical or legal …
of human consent and/or presence for transactions held by any number of physical or legal …
Similarity Distance Learning on SPD Manifold for Writer Independent Offline Signature Verification
EN Zois, D Tsourounis, D Kalivas - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Identifying the existence or approval of a human in a number of past, recent and present day
activities with the use of a handwritten signature is a captivating biometric challenge …
activities with the use of a handwritten signature is a captivating biometric challenge …
Leveraging Expert Models for Training Deep Neural Networks in Scarce Data Domains: Application to Offline Handwritten Signature Verification
This paper introduces a novel approach to leverage the knowledge of existing expert
models for training new Convolutional Neural Networks, on domains where task-specific …
models for training new Convolutional Neural Networks, on domains where task-specific …
Janus-Faced Handwritten Signature Attack: A Clash Between a Handwritten Signature Duplicator and a Writer Independent, Metric Meta-learning Offline Signature …
Signature verification is a popular research area. SigmML, a new system for offline, writer-
independent verification, has been developed, offering a unique approach outside typical …
independent verification, has been developed, offering a unique approach outside typical …
Neural Networks: deep learning strategies for problems with limited data
Small sample size learning (SSSL) problem arises when the available training data are
limited, making it challenging for machine learning models to capture meaningful patterns …
limited, making it challenging for machine learning models to capture meaningful patterns …