Zobrazeno 1 - 10
of 153
pro vyhledávání: '"face biometrics"'
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 9, Iss 2, Pp 467-480 (2024)
Abstract Facial beauty analysis is an important topic in human society. It may be used as a guidance for face beautification applications such as cosmetic surgery. Deep neural networks (DNNs) have recently been adopted for facial beauty analysis and
Externí odkaz:
https://doaj.org/article/e2a5663f845f40fcb134cb2f23d09ce6
Autor:
Mohamed Oulad-Kaddour, Hamid Haddadou, Daniel Palacios-Alonso, Cristina Conde, Enrique Cabello
Publikováno v:
EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, Vol 11, Iss 2 (2024)
The world has lived an exceptional time period caused by the Coronavirus pandemic. To limit Covid-19 propagation, governments required people to wear a facial mask outside. In facial data analysis, mask-wearing on the human face creates predominant o
Externí odkaz:
https://doaj.org/article/e9981e38005c4cf189f1ff843a5241a1
An image‐based facial acupoint detection approach using high‐resolution network and attention fusion
Publikováno v:
IET Biometrics, Vol 12, Iss 3, Pp 146-158 (2023)
Abstract With the prevalence of Traditional Chinese Medicine (TCM), automation techniques are highly required to support the therapy and save human resources. As the fundamental of the TCM treatment, acupoint detection is attracting research attentio
Externí odkaz:
https://doaj.org/article/4ddffb6859a7450781c4ddccd63e9ba9
Publikováno v:
Sensors, Vol 24, Iss 9, p 2750 (2024)
Biometric authentication plays a vital role in various everyday applications with increasing demands for reliability and security. However, the use of real biometric data for research raises privacy concerns and data scarcity issues. A promising appr
Externí odkaz:
https://doaj.org/article/888c4df8cffb4a768452ccabc6b1a097
Autor:
Mohamed Oulad-Kaddour, Hamid Haddadou, Cristina Conde, Daniel Palacios-Alonso, Enrique Cabello
Publikováno v:
Advances in Distributed Computing and Artificial Intelligence Journal, Vol 11, Iss 3, Pp 249-261 (2023)
Gender classification is an important biometric task. It has been widely studied in the literature. Face modality is the most studied aspect of human-gender classification. Moreover, the task has also been investigated in terms of different face comp
Externí odkaz:
https://doaj.org/article/f0ec41b7788e4cfaa3d3cb447a50e360
Akademický článek
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Publikováno v:
IET Biometrics, Vol 11, Iss 4, Pp 279-288 (2022)
Abstract Head pose estimation (HPE) notoriously represents a crucial task for many computer vision applications in robotics, biometry and video surveillance. While, in general, HPE can be performed on both still images and frames extracted from live
Externí odkaz:
https://doaj.org/article/2b218b641a514cb884da71b6e0d803e6
Publikováno v:
IET Biometrics, Vol 11, Iss 3, Pp 260-276 (2022)
Abstract In recent years, with the advent of deep‐learning, face recognition (FR) has achieved exceptional success. However, many of these deep FR models perform much better in handling frontal faces compared to profile faces. The major reason for
Externí odkaz:
https://doaj.org/article/bc784d1fa9524904839aa2831eb01734
Autor:
Pedro C. Pedro Neto, Joao Ribeiro Pinto, Fadi Boutros, Naser Damer, Ana F. Sequeira, Jaime S. Cardoso
Publikováno v:
IEEE Access, Vol 10, Pp 86222-86233 (2022)
Over the years, the evolution of face recognition (FR) algorithms has been steep and accelerated by a myriad of factors. Motivated by the unexpected elements found in real-world scenarios, researchers have investigated and developed a number of metho
Externí odkaz:
https://doaj.org/article/5cb8fefa506f4c1980843389a9c8cdc8
Autor:
Ramachandra Raghavendra, Guoqiang Li
Publikováno v:
IEEE Access, Vol 10, Pp 82418-82433 (2022)
Face morphing attacks have demonstrated a high vulnerability on human observers and commercial off-the-shelf Face Recognition Systems (FRS), especially in the border control scenario. Therefore, detecting face morphing attacks is paramount to achievi
Externí odkaz:
https://doaj.org/article/d09b9741b4b14252a023eff619c19a91