Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Machine learning-based offline signature verification systems: A systematic review
The offline signatures are the most widely adopted biometric authentication techniques in
banking systems, administrative and financial applications due to its simplicity and …
banking systems, administrative and financial applications due to its simplicity and …
A new wrapper feature selection method for language-invariant offline signature verification
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 …
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
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 …
authentication of a person based on their original samples. In offline signature verification …
From text to signatures: Knowledge transfer for efficient deep feature learning in offline signature verification
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 …
or the consent of a person. Offline Signature Verification (OSV) is the task of verifying the …
Deep learning-based data augmentation method and signature verification system for offline handwritten signature
Offline handwritten signature verification is a challenging pattern recognition task. One of the
most significant limitations of the handwritten signature verification problem is inadequate …
most significant limitations of the handwritten signature verification problem is inadequate …
Signature identification and verification techniques: state-of-the-art work
Signature identification and verification are some of the biometric systems used for personal
identification. Signatures can be considered as authentication of an individual by the …
identification. Signatures can be considered as authentication of an individual by the …
A multi-task approach for contrastive learning of handwritten signature feature representations
In spite of recent advances in computer vision, the classic problem of offline handwritten
signature verification still remains challenging. The signature verification task has a high …
signature verification still remains challenging. The signature verification task has a high …
A two-tier ensemble approach for writer dependent online signature verification
Biometric verification systems are used to recognize people based on their uniqueness or
characteristics. Signature is considered as one of the most commonly used biometric that …
characteristics. Signature is considered as one of the most commonly used biometric that …
Learning the micro deformations by max-pooling for offline signature verification
For signature verification systems, micro deformations can be defined as the small
differences in the same strokes of signatures or special writing habits of different signers …
differences in the same strokes of signatures or special writing habits of different signers …