Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Naif Alajlan"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-15 (2023)
Abstract Scene classification is a crucial research problem in remote sensing (RS) that has attracted many researchers recently. It has many challenges due to multiple issues, such as: the complexity of remote sensing scenes, the classes overlapping
Externí odkaz:
https://doaj.org/article/165169ca5d3f4f899333a12f68a3324e
Autor:
Mohamad M. Al Rahhal, Yakoub Bazi, Norah A. Alsharif, Laila Bashmal, Naif Alajlan, Farid Melgani
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 9115-9126 (2022)
Cross-modal text-image retrieval in remote sensing (RS) provides a flexible retrieval experience for mining useful information from RS repositories. However, existing methods are designed to accept queries formulated in the English language only, whi
Externí odkaz:
https://doaj.org/article/6f63226a433d4cf98d007509067e18aa
Publikováno v:
Journal of Imaging, Vol 9, Iss 9, p 168 (2023)
Unimodal biometric systems rely on a single source or unique individual biological trait for measurement and examination. Fingerprint-based biometric systems are the most common, but they are vulnerable to presentation attacks or spoofing when a fake
Externí odkaz:
https://doaj.org/article/1e240dd55e9e45818e6210fe8b208334
Publikováno v:
Applied Sciences, Vol 13, Iss 5, p 3070 (2023)
The electrocardiogram (ECG) signal is shown to be promising as a biometric. To this end, it has been demonstrated that the analysis of ECG signals can be considered as a good solution for increasing the biometric security levels. This can be mainly d
Externí odkaz:
https://doaj.org/article/e8d7812b4a344e5b8bc5fcea6b5a272b
Publikováno v:
Data, Vol 7, Iss 10, p 141 (2022)
The electrocardiogram (ECG) signal produced by the human heart is an emerging biometric modality that can play an important role in the future generation’s identity recognition with the support of machine learning techniques. One of the major obsta
Externí odkaz:
https://doaj.org/article/da4e19c987d6497abc776752abcb21ae
Publikováno v:
IEEE Access, Vol 7, Pp 119873-119880 (2019)
The multi-label classification problem in Unmanned Aerial Vehicle (UAV) images is particularly challenging compared to single-label classification due to its combinatorial nature. To tackle this issue, we propose in this paper a deep learning approac
Externí odkaz:
https://doaj.org/article/4544ee0b2eae43f89ef651ab1a92f422
Publikováno v:
IEEE Access, Vol 7, Pp 182225-182237 (2019)
In this paper, we propose a novel end-to-end learnable architecture based on Dense Convolutional Networks (DCN) for the classification of electrocardiogram (ECG) signals. This architecture is based on two main modules: the first is a generative modul
Externí odkaz:
https://doaj.org/article/5fc1fc67918a4986a043dfc902371c3e
Publikováno v:
Remote Sensing, Vol 13, Iss 19, p 3861 (2021)
We present a new method for multi-source semi-supervised domain adaptation in remote sensing scene classification. The method consists of a pre-trained convolutional neural network (CNN) model, namely EfficientNet-B3, for the extraction of highly dis
Externí odkaz:
https://doaj.org/article/fa7e44efba79443f9ca5dad77296697d
Publikováno v:
Entropy, Vol 23, Iss 8, p 1089 (2021)
With the rapid growth of fingerprint-based biometric systems, it is essential to ensure the security and reliability of the deployed algorithms. Indeed, the security vulnerability of these systems has been widely recognized. Thus, it is critical to e
Externí odkaz:
https://doaj.org/article/505d4e60564e454492daffe527f620d0
Publikováno v:
IEEE Access, Vol 5, Pp 1753-1761 (2017)
The heart is potentially a highly secured biometric modality. Although many templates have been proposed to be extracted from heart-signal for biometric authentication, they have yet to reach a single digit equal error rate (EER) of false matches and
Externí odkaz:
https://doaj.org/article/b313bbd8a4364610aa02b6c55dc8f044