Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Tiago Roxo"'
Publikováno v:
IEEE Access, Vol 12, Pp 61113-61136 (2024)
Deep Learning is currently used to perform multiple tasks, such as object recognition, face recognition, and natural language processing. However, Deep Neural Networks (DNNs) are vulnerable to perturbations that alter the network prediction, named ad
Externí odkaz:
https://doaj.org/article/0a34e964ebae44ae813ca6d388382a1e
Publikováno v:
IEEE Access, Vol 10, Pp 59125-59134 (2022)
Cybercrime affects companies worldwide, costing millions of dollars annually. The constant increase of threats and vulnerabilities raises the need to handle vulnerabilities in a prioritized manner. This prioritization can be achieved through Common V
Externí odkaz:
https://doaj.org/article/53185033dd2842a88e236cdea17a7c2d
Autor:
Tiago Roxo, Hugo Proenca
Publikováno v:
IEEE Access, Vol 10, Pp 28122-28132 (2022)
Soft biometrics inference in surveillance scenarios is a topic of interest for various applications, particularly in security-related areas. However, soft biometric analysis is not extensively reported in wild conditions. In particular, previous work
Externí odkaz:
https://doaj.org/article/ad938a3172fc434e94b52dc8d6fc2cde
Publikováno v:
In Telematics and Informatics November 2024 95
Autor:
Tiago Roxo, Hugo Proença
Publikováno v:
IEEE Transactions on Biometrics, Behavior, and Identity Science. 3:573-582
Soft biometrics analysis is seen as an important research topic, given its relevance to various applications. However, even though it is frequently seen as a solved task, it can still be very hard to perform in wild conditions, under varying image co
Autor:
Tiago Roxo, Hugo Proenca
Soft biometrics inference in surveillance scenarios is a topic of interest for various applications, particularly in security-related areas. However, soft biometric analysis is not extensively reported in wild conditions. In particular, previous work
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eba32e5757eb0e51119f5a9d6f9ce030
http://arxiv.org/abs/2107.06847
http://arxiv.org/abs/2107.06847