Zobrazeno 1 - 10
of 1 547
pro vyhledávání: '"convolutional autoencoder"'
Autor:
HE Jia
Publikováno v:
Chengshi guidao jiaotong yanjiu, Vol 27, Iss 10, Pp 13-20 (2024)
Objective The diverse and complex operating environment of axle box bearings makes it challenging for bearing fault diagnostic methods to achieve satisfactory results with the single sensor. To address this issue, research is conducted on train beari
Externí odkaz:
https://doaj.org/article/9fd129fe371b49c6a3384594b97ba127
Publikováno v:
AIMS Mathematics, Vol 9, Iss 7, Pp 17676-17695 (2024)
The fast development of the internet of things has been associated with the complex worldwide problem of protecting interconnected devices and networks. The protection of cyber security is becoming increasingly complicated due to the enormous growth
Externí odkaz:
https://doaj.org/article/70ff11a1d438471ba0570f1e62c30cef
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
IntroductionAdolescence is a fundamental period of transformation, encompassing extensive physical, psychological, and behavioral changes. Effective health risk assessment during this stage is crucial for timely intervention, yet traditional methodol
Externí odkaz:
https://doaj.org/article/7e665edbb7b24faf972c7fe95a652ce0
Autor:
Emilio Corcione, Fabian Jakob, Lukas Wagner, Raphael Joos, Andre Bisquerra, Marcel Schmidt, Andreas D. Wieck, Arne Ludwig, Michael Jetter, Simone L. Portalupi, Peter Michler, Cristina Tarín
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract A key challenge in quantum photonics today is the efficient and on-demand generation of high-quality single photons and entangled photon pairs. In this regard, one of the most promising types of emitters are semiconductor quantum dots, fluor
Externí odkaz:
https://doaj.org/article/de516114492d4a43929e441ae9c5cca7
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 129, Iss , Pp 103864- (2024)
Hyperspectral unmixing is a key technology in the development of remote sensing applications. However, since both endmembers and abundances are unknown, unmixing is a non-convex problem with a large solution space. To solve this, existing methods usu
Externí odkaz:
https://doaj.org/article/aa7533b7fbf447e1a8b51942e4c8c5f4
Publikováno v:
IEEE Access, Vol 12, Pp 146441-146452 (2024)
The exploration and implementation of brain-computer interfaces (BCIs) utilizing electro- encephalography (EEG) are becoming increasingly widespread. However, their safety considerations have received scant attention. Recent studies have shown that E
Externí odkaz:
https://doaj.org/article/b44db8190002499a84fd5e3198065d91
Autor:
Moshiur Rahman Tonmoy, Abdul Fattah Rakib, Rashik Rahman, Md. Akhtaruzzaman Adnan, M. F. Mridha, Jie Huang, Jungpil Shin
Publikováno v:
IEEE Open Journal of the Computer Society, Vol 5, Pp 120-130 (2024)
Font style recognition plays a vital role in the field of computer vision, particularly in document and pattern analysis, and image processing. In the industry context, this recognition of font styles holds immense importance for professionals such a
Externí odkaz:
https://doaj.org/article/db41d852b44e4636894fe90fc63cd981
Autor:
Jianbin Zheng, Ziyao Chen, Liping Huang, Yifan Gao, Xiangxiang Yu, Hui Wang, Jiamei Yang, Yu Wang
Publikováno v:
IEEE Access, Vol 12, Pp 22144-22157 (2024)
In recent years, with the rapid advancements in deep learning technologies, particularly deep neural networks, signature verification has seen significant improvements in accuracy. Despite the significant progress made in using deep learning technolo
Externí odkaz:
https://doaj.org/article/69210d073ce6434f8a334c7430fb77c7
Publikováno v:
Energies, Vol 17, Iss 16, p 4098 (2024)
Renewable energy accommodation in power grids leads to frequent load changes in power plants. Sensitive turbine fault monitoring technology is critical to ensure the stable operation of the power system. Existing techniques do not use information suf
Externí odkaz:
https://doaj.org/article/c4dccab0c4c6440f9b27607498479373
Publikováno v:
Frontiers in Manufacturing Technology, Vol 4 (2024)
Introduction: Conventional defect detection systems in Automated Fibre Placement (AFP) typically rely on end-to-end supervised learning, necessitating a substantial number of labelled defective samples for effective training. However, the scarcity of
Externí odkaz:
https://doaj.org/article/89c0b2a6270840cf8108d5050d8e23cb