Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Ruofan Zhang"'
Publikováno v:
Tongxin xuebao, Vol 44, Pp 103-111 (2023)
In order to alleviate the spectrum scarcity and capacity limitation of the current wireless system, the terahertz frequency band was introduced and the reconfigurable intelligent surface (RIS) was used for auxiliary communication to construct a downl
Externí odkaz:
https://doaj.org/article/72fef6d9b285411494eec90be802dfda
Autor:
Fatang CHEN, Ruofan ZHANG
Publikováno v:
Tongxin xuebao, Vol 44, Pp 70-78 (2023)
In order to meet the higher requirements of vehicle communication quality and spectral efficiency, a IoV resource allocation algorithm assisted by reconfigurable intelligent surface (RIS) was proposed.The RIS reflection coefficient matrix, power allo
Externí odkaz:
https://doaj.org/article/c90c87a78542493686f059a5934f42d6
Publikováno v:
Applied Sciences, Vol 14, Iss 13, p 5524 (2024)
Currently, few deep models are applied to pepper-picking detection, and existing generalized neural networks face issues such as large model parameters, prolonged training times, and low accuracy. To address these challenges, this paper proposes the
Externí odkaz:
https://doaj.org/article/a95c4af317dd4d3eacfee578dc8f3391
Publikováno v:
Sensors, Vol 24, Iss 8, p 2464 (2024)
Deep learning methodologies employed for biomass prediction often neglect the intricate relationships between labels and samples, resulting in suboptimal predictive performance. This paper introduces an advanced supervised contrastive learning techni
Externí odkaz:
https://doaj.org/article/0a8cff5e78d44614983f5fff1dff2bea
Autor:
Ruofan Zhang, Lixia Xi, Jiacheng Wei, Jiayun Deng, Shucheng Du, Wenbo Zhang, Xiaoguang Zhang, Xiaosheng Xiao
Publikováno v:
IEEE Photonics Journal, Vol 15, Iss 3, Pp 1-8 (2023)
Nonlinear frequency division multiplexing (NFDM) system is an optional candidate to overcome the fiber nonlinearity limit. A full-spectrum modulated NFDM system, modulating data on combined continuous spectrum (CS) and discrete spectrum (DS) together
Externí odkaz:
https://doaj.org/article/d25ed48f10874f0790e3065ba3967261
Publikováno v:
Pharmacological Research, Vol 194, Iss , Pp 106865- (2023)
Succinate is a vital signaling metabolite produced by the host and gut microbiota. Succinate has been shown to regulate host metabolic homeostasis and inhibit obesity-associated inflammation in macrophages by engaging its cognate receptor, SUCNR1. Ho
Externí odkaz:
https://doaj.org/article/46611c1287c54e7597e88fb926ec9465
Publikováno v:
Space: Science & Technology, Vol 3 (2023)
This paper reports a numerical research on MEMS (microelectromechanical system) micronozzles through multiphysics coupling simulation along with design optimization based on simulation results. The micronozzle, which is a core component of the electr
Externí odkaz:
https://doaj.org/article/6d30c2b1822e4ea7ac159e1b6b0d6c28
Publikováno v:
Applied Sciences, Vol 13, Iss 9, p 5589 (2023)
The current neural networks for tomato leaf disease recognition have problems such as large model parameters, long training time, and low model accuracy. To solve these problems, a lightweight convolutional neural network (LBFNet) is proposed in this
Externí odkaz:
https://doaj.org/article/4653dd5e07674f31960fe02f2deb3ca9
Publikováno v:
Applied Sciences, Vol 13, Iss 8, p 4928 (2023)
In this study, computer vision applicable to traditional agriculture was used to achieve accurate identification of rice leaf diseases with complex backgrounds. The researchers developed the RiceDRA-Net deep residual network model and used it to iden
Externí odkaz:
https://doaj.org/article/962f67cf027f4c45a5ea3e8166db6ad0
Publikováno v:
Applied Sciences, Vol 13, Iss 7, p 4348 (2023)
Tomatoes are a crop of significant economic importance, and disease during growth poses a substantial threat to yield and quality. In this paper, we propose IBSA_Net, a tomato leaf disease recognition network that employs transfer learning and small
Externí odkaz:
https://doaj.org/article/b6840035d650426b959ee5856e1fbf31