Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Juan E. Tapia"'
Publikováno v:
IEEE Access, Vol 12, Pp 68573-68585 (2024)
The accurate detection of ID card Presentation Attacks (PA) is becoming increasingly important due to the rising number of online/remote services that require the presentation of digital photographs of ID cards for digital onboarding or authenticatio
Externí odkaz:
https://doaj.org/article/d0fbc95b26b8484c9094a7aa5462827a
Publikováno v:
IET Biometrics, Vol 2024 (2024)
Gender classification on normalized iris images has been previously attempted with varying degrees of success. In these previous studies, it has been shown that occlusion masks may introduce gender information; occlusion masks are used in iris recogn
Externí odkaz:
https://doaj.org/article/804272c5014a463fb86d5d07a509548d
Autor:
Daniel P. Benalcazar, Juan E. Tapia, Mauricio Vasquez, Leonardo Causa, Enrique Lopez Droguett, Christoph Busch
Publikováno v:
IEEE Access, Vol 11, Pp 133577-133590 (2023)
Iris Recognition (IR) is one of the market’s most reliable and accurate biometric systems. Today, it is challenging to build NearInfraRed (NIR) capturing devices under the premise of hardware price reduction. Commercial NIR sensors are protected fr
Externí odkaz:
https://doaj.org/article/e47e1add59ff4931aa9f9b6336e6395e
Publikováno v:
IET Biometrics, Vol 11, Iss 4, Pp 343-354 (2022)
Abstract The LivDet‐2020 competition focuses on Presentation Attacks Detection (PAD) algorithms, has still open problems, mainly unknown attack scenarios. It is crucial to enhance PAD methods. This can be achieved by augmenting the number of Presen
Externí odkaz:
https://doaj.org/article/83fbc7ab65bd4f358a0e06e5011a23b9
Publikováno v:
IEEE Access, Vol 10, Pp 67573-67589 (2022)
Selfie-based biometrics has great potential for a wide range of applications since, e.g. periocular verification is contactless and is safe to use in pandemics such as COVID-19, when a major portion of a face is covered by a facial mask. Despite its
Externí odkaz:
https://doaj.org/article/67b7197f397442538178150225631a04
Autor:
Juan E. Tapia, Enrique Lopez Droguett, Andres Valenzuela, Daniel P. Benalcazar, Leonardo Causa, Christoph Busch
Publikováno v:
IEEE Access, Vol 9, Pp 109732-109744 (2021)
This paper proposes a new framework to detect, segment, and estimate the localization of the eyes from a periocular Near-Infra-Red iris image under alcohol consumption. This stage will take part in the final solution to measure the fitness for duty.
Externí odkaz:
https://doaj.org/article/7405b70e1a3948a499ecfdca095a9d02
Autor:
Juan E. Tapia, Christoph Busch
Publikováno v:
IEEE Access, Vol 9, Pp 167628-167641 (2021)
Face morphing attack detection is a challenging task. Automatic classification methods and manual inspection are realised in automatic border control gates to detect morphing attacks. Understanding how a machine learning system can detect morphed fac
Externí odkaz:
https://doaj.org/article/dd582c838a2b4ffb9f29e3c6020965c3
Publikováno v:
IEEE Access, Vol 8, Pp 171598-171607 (2020)
Semantic segmentation has been widely used for several applications, including the detection of eye structures. This is used in tasks such as eye-tracking and gaze estimation, which are useful techniques for human-computer interfaces, salience detect
Externí odkaz:
https://doaj.org/article/5a45e36151cb4967b9429dcf112e4d4a
Autor:
Juan E. Tapia, Claudio A. Perez
Publikováno v:
IEEE Access, Vol 7, Pp 29114-29127 (2019)
In the past few years, accuracy in determining gender from iris images has increased significantly, approaching levels that make novel applications of this biometric technology feasible. In this paper, we report the gender classification rate by usin
Externí odkaz:
https://doaj.org/article/317935cc364d45d796cff2402785d906
Autor:
Juan E. Tapia, Claudio A. Perez
Publikováno v:
IEEE Access, Vol 7, Pp 79374-79387 (2019)
Face recognition performance by computers has been shown to be more accurate than that of humans. However, a bias with soft-biometrics features has been detected. This bias reduces recognition performance when gender is used. Feature selection for ge
Externí odkaz:
https://doaj.org/article/0d3047e6d67744c58b471bbe4b4f5f00