Machine learning-based offline signature verification systems: A systematic review

MM Hameed, R Ahmad, MLM Kiah… - Signal Processing: Image …, 2021 - Elsevier
The offline signatures are the most widely adopted biometric authentication techniques in
banking systems, administrative and financial applications due to its simplicity and …

A high precision intrusion detection system for network security communication based on multi-scale convolutional neural network

J Yu, X Ye, H Li - Future Generation Computer Systems, 2022 - Elsevier
The openness of network data makes it vulnerable to hackers, viruses and other attacks,
which seriously threatens the privacy and property security of users. In order to improve the …

CBCapsNet: A novel writer-independent offline signature verification model using a CNN-based architecture and capsule neural networks

E Parcham, M Ilbeygi, M Amini - Expert Systems with Applications, 2021 - Elsevier
Offline Signature verification is a biometric method with important applications in financial,
legal and administrative procedures. The verification process includes comparing the …

A new wrapper feature selection method for language-invariant offline signature verification

D Banerjee, B Chatterjee, P Bhowal… - Expert Systems with …, 2021 - Elsevier
Among various biometric systems, an offline signature verification system has been widely
used in all fields such as in banks, educational institutes, legal procedures and, criminal …

Offline signature verification system: a novel technique of fusion of GLCM and geometric features using SVM

FE Batool, M Attique, M Sharif, K Javed, M Nazir… - Multimedia Tools and …, 2024 - Springer
In the area of digital biometric systems, the handwritten signature plays a key role in the
authentication of a person based on their original samples. In offline signature verification …

A review of signature recognition using machine learning

EA Soelistio, REH Kusumo, ZV Martan… - 2021 1st International …, 2021 - ieeexplore.ieee.org
Signatures have been used for years for transactions and consenting to responsibilities. Yet,
online or offline, signatures can easily be falsified as there are no security measures in place …

[HTML][HTML] COVID-19: a new deep learning computer-aided model for classification

OM Elzeki, M Shams, S Sarhan, M Abd Elfattah… - PeerJ Computer …, 2021 - peerj.com
Chest X-ray (CXR) imaging is one of the most feasible diagnosis modalities for early
detection of the infection of COVID-19 viruses, which is classified as a pandemic according …

DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning …

J Yang, M Shokouhifar, L Yee, AA Khan… - Expert Systems with …, 2024 - Elsevier
Identifying and verifying the identity of people based on scanned images of handwritten
documents is an applicable biometric modality with applications in forensic and historic …

CapsNet regularization and its conjugation with ResNet for signature identification

M Jampour, S Abbaasi, M Javidi - Pattern Recognition, 2021 - Elsevier
We propose a new regularization term for CapsNet that significantly improves the
generalization power of the original method from small training data while requiring much …

Forgery-free signature verification with stroke-aware cycle-consistent generative adversarial network

J Jiang, S Lai, L Jin, Y Zhu, J Zhang, B Chen - Neurocomputing, 2022 - Elsevier
In recent years, the performance of handwritten signature verification (HSV) has been
considerably improved by deep learning methods. However, deep HSV still faces significant …