Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Jaswal, Gaurav"'
Autor:
Tandon, Abhishek, Sharma, Geetanjali, Jaswal, Gaurav, Nigam, Aditya, Ramachandra, Raghavendra
Recent studies have emphasized the potential of forehead-crease patterns as an alternative for face, iris, and periocular recognition, presenting contactless and convenient solutions, particularly in situations where faces are covered by surgical mas
Externí odkaz:
http://arxiv.org/abs/2408.15693
Biometric authentication, which utilizes contactless features, such as forehead patterns, has become increasingly important for identity verification and access management. The proposed method is based on learning a 3D spatio-spatial temporal convolu
Externí odkaz:
http://arxiv.org/abs/2403.16202
Face morphing attacks have emerged as a potential threat, particularly in automatic border control scenarios. Morphing attacks permit more than one individual to use travel documents that can be used to cross borders using automatic border control ga
Externí odkaz:
http://arxiv.org/abs/2303.14004
Autor:
Salazar-Jurado, Edwin H., Hernández-García, Ruber, Vilches-Ponce, Karina, Barrientos, Ricardo J., Mora, Marco, Jaswal, Gaurav
Publikováno v:
Information Fusion 89 (2023) 66-90
With the recent success of computer vision and deep learning, remarkable progress has been achieved on automatic personal recognition using vein biometrics. However, collecting large-scale real-world training data for palm vein recognition has turned
Externí odkaz:
http://arxiv.org/abs/2205.10179
An iris presentation attack detection (IPAD) is essential for securing personal identity is widely used iris recognition systems. However, the existing IPAD algorithms do not generalize well to unseen and cross-domain scenarios because of capture in
Externí odkaz:
http://arxiv.org/abs/2111.00919
Current finger knuckle image recognition systems, often require users to place fingers' major or minor joints flatly towards the capturing sensor. To extend these systems for user non-intrusive application scenarios, such as consumer electronics, for
Externí odkaz:
http://arxiv.org/abs/1904.01289
At present spoofing attacks via which biometric system is potentially vulnerable against a fake biometric characteristic, introduces a great challenge to recognition performance. Despite the availability of a broad range of presentation attack detect
Externí odkaz:
http://arxiv.org/abs/1812.07444
Designing an end-to-end deep learning network to match the biometric features with limited training samples is an extremely challenging task. To address this problem, we propose a new way to design an end-to-end deep CNN framework i.e., PVSNet that w
Externí odkaz:
http://arxiv.org/abs/1812.06271
FDFNet : A Secure Cancelable Deep Finger Dorsal Template Generation Network Secured via. Bio-Hashing
Present world has already been consistently exploring the fine edges of online and digital world by imposing multiple challenging problems/scenarios. Similar to physical world, personal identity management is very crucial in-order to provide any secu
Externí odkaz:
http://arxiv.org/abs/1812.05308