Zobrazeno 11 - 20
of 2 404
pro vyhledávání: '"Zhao, Xiaoyu"'
Temperature field prediction is of great importance in the thermal design of systems engineering, and building the surrogate model is an effective way for the task. Generally, large amounts of labeled data are required to guarantee a good prediction
Externí odkaz:
http://arxiv.org/abs/2301.06674
The application of transformation optics to the development of intriguing electromagnetic devices can produce weakly anisotropic or isotropic media with the assistance of quasi-conformal and/or conformal mapping, as opposed to the strongly anisotropi
Externí odkaz:
http://arxiv.org/abs/2301.00352
With the flourishing development of nanophotonics, Cherenkov radiation pattern can be designed to achieve superior performance in particle detection by fine-tuning the properties of metamaterials such as photonic crystals (PCs) surrounding the swift
Externí odkaz:
http://arxiv.org/abs/2211.15117
Autor:
Wu Yingping, Lu Lizhi, Li Haiying, Chen Li, Gu Tiantian, Zhao Xiaoyu, Yao Yingying, Li Jiahui
Publikováno v:
Poultry Science, Vol 103, Iss 6, Pp 103724- (2024)
ABSTRACT: Sertoli cells (SC) are a type of important cells in the testes, which can provide transport proteins, regulatory proteins, growth factors, and other cytokines for the spermatogenic process. They participate in the regulation of the maturati
Externí odkaz:
https://doaj.org/article/e8694494fd144d649bb6f3bf1636562a
Autor:
Leng, Yixuan, Zhao, Xiaoyu
Publikováno v:
Journal of Business & Industrial Marketing, 2023, Vol. 38, Issue 12, pp. 2545-2560.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JBIM-05-2022-0224
Autor:
Chen, Anqi1 (AUTHOR) 18800017599@163.com, Zhao, Xiaoyu2 (AUTHOR) xrnmyfzx@bdxrkj.com, Zhao, Xiurong1 (AUTHOR) zxiurong_feign@163.com, Wang, Gang1 (AUTHOR) wanggang@cau.edu.cn, Zhang, Xinye1 (AUTHOR) xinye_leaf@163.com, Ren, Xufang1 (AUTHOR) rxf1828@163.com, Zhang, Yalan1 (AUTHOR) 15901003721@163.com, Cheng, Xue1 (AUTHOR) chengxue@cau.edu.cn, Yu, Xiaofan1 (AUTHOR) b20233040354@cau.edu.cn, Wang, Huie3 (AUTHOR) whedky@126.com, Guo, Menghan1 (AUTHOR) sy20233040865@cau.edu.cn, Jiang, Xiaoyu1 (AUTHOR) jxy1581908148@163.com, Mei, Xiaohan1 (AUTHOR) 2022333020320@cau.edu.cn, Wei, Guozhen4 (AUTHOR) 17866705322@163.com, Wang, Xue5 (AUTHOR) vvetwangxue6307@sina.com, Jiang, Runshen6 (AUTHOR) jiangrunshen@ahau.edu.cn, Guo, Xing6 (AUTHOR) guoxing0405@126.com, Ning, Zhonghua1 (AUTHOR) ningzhh@cau.edu.cn, Qu, Lujiang1,3 (AUTHOR) quluj@163.com
Publikováno v:
Animals (2076-2615). Jun2024, Vol. 14 Issue 12, p1780. 10p.
As a powerful way of realizing semi-supervised segmentation, the cross supervision method learns cross consistency based on independent ensemble models using abundant unlabeled images. However, the wrong pseudo labeling information generated by cross
Externí odkaz:
http://arxiv.org/abs/2203.05118
Few-shot segmentation enables the model to recognize unseen classes with few annotated examples. Most existing methods adopt prototype learning architecture, where support prototype vectors are expanded and concatenated with query features to perform
Externí odkaz:
http://arxiv.org/abs/2203.04095
For the temperature field reconstruction (TFR), a complex image-to-image regression problem, the convolutional neural network (CNN) is a powerful surrogate model due to the convolutional layer's good image feature extraction ability. However, a lot o
Externí odkaz:
http://arxiv.org/abs/2202.06596
Physical field reconstruction is highly desirable for the measurement and control of engineering systems. The reconstruction of the temperature field from limited observation plays a crucial role in thermal management for electronic equipment. Deep l
Externí odkaz:
http://arxiv.org/abs/2201.10860