Zobrazeno 1 - 10
of 127
pro vyhledávání: '"Bakhtiar Affendi"'
Autor:
Liew Pei Yi, Muhammad Firdaus Akbar, Mohd Nadhir Ab Wahab, Bakhtiar Affendi Rosdi, Mohd Akashah Fauthan, Nawaf H. M. M. Shrifan
Publikováno v:
IEEE Access, Vol 12, Pp 84706-84725 (2024)
The demand for solid wood is high in the construction and manufacturing industries, and the quality of the wood is crucial. Defects in solid wood can result in hazardous accidents or financial loss. While manual visual inspection of defects is time c
Externí odkaz:
https://doaj.org/article/23cc78c084d44c788c6a974242b9ef0d
Publikováno v:
PeerJ Computer Science, Vol 10, p e1837 (2024)
Several deep neural networks have been introduced for finger vein recognition over time, and these networks have demonstrated high levels of performance. However, most current state-of-the-art deep learning systems use networks with increasing layers
Externí odkaz:
https://doaj.org/article/2d2711e0daaf4095a5c2b71689fb854b
Autor:
Tian Zhonglin, Mohd Nadhir Ab Wahab, Muhammad Firdaus Akbar, Ahmad Sufril Azlan Mohamed, Mohd Halim Mohd Noor, Bakhtiar Affendi Rosdi
Publikováno v:
IEEE Access, Vol 11, Pp 76827-76841 (2023)
Standard Multi-Object Tracking (MOT) frameworks are currently categorised into three categories: tracking-by-detection, joint detection, and tracking and attention mechanisms. Infrequently, the latter two frameworks require substantial computing reso
Externí odkaz:
https://doaj.org/article/e1d865e53de64822b30c373ac95d1e71
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 3, Pp 646-656 (2022)
Finger vein identification is a recently developed biometric technology and has become an essential field in biometrics, garnering increasing attention in recent years. As a biometric trait, using vein patterns allows for personal recognition with hi
Externí odkaz:
https://doaj.org/article/2d1976e04c3b42028cadb52f15433ed1
Publikováno v:
Applied Sciences, Vol 13, Iss 13, p 7433 (2023)
Hand detection and tracking are key components in many computer vision applications, including hand pose estimation and gesture recognition for human–computer interaction systems, virtual reality, and augmented reality. Despite their importance, re
Externí odkaz:
https://doaj.org/article/65db124633694d81b765aa0f515f7b9f
Publikováno v:
IEEE Access, Vol 7, Pp 5874-5885 (2019)
In this paper, an efficient finger vein recognition algorithm based on the combination of the nearest centroid neighbor and sparse representation classification techniques ( ${k}$ NCN-SRC) is presented. The previously proposed recognition algorithms
Externí odkaz:
https://doaj.org/article/8c461de779f54e48bfefa63f6b25cf1d
Publikováno v:
IEEE Access, Vol 7, Pp 132966-132978 (2019)
Currently, the used of deep learning method has attracted widespread attention in machine learning, especially in Biometric. Many deep learning methods have been proposed like convolutional neural network (CNN), AlexNet and principal component analys
Externí odkaz:
https://doaj.org/article/e5fdd5b12f954f89bde95de2013393cf
Publikováno v:
Sensors, Vol 11, Iss 12, Pp 11357-11371 (2011)
In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body.
Externí odkaz:
https://doaj.org/article/aeb10d04b7244dba9dc21db7676120b9
Publikováno v:
In Journal of King Saud University - Computer and Information Sciences March 2022 34(3):646-656
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