Zobrazeno 1 - 10
of 251
pro vyhledávání: '"Li Jiazhi"'
Autor:
Li Jiazhi, Cao Peihua, Chen Zhenhu, Deng Ruihua, Nie Yu, Pang Feixiong, Liu Xiaomian, Huang Haijia, Yang Jianrong, Zhong Kebo, Lai Yanhua
Publikováno v:
Open Medicine, Vol 19, Iss 1, Pp e0273496-41 (2024)
This study aimed to evaluate the efficacy and safety of solid organ transplantation recipients inoculated with an inactivated COVID-19 vaccine.
Externí odkaz:
https://doaj.org/article/95bb78cdf6c94a8c9b841fe41c18d38a
UI-to-code technology has streamlined the front-end development process, reducing repetitive tasks for engineers. prior research mainly use design prototypes as inputs, with the effectiveness of the generated code heavily dependent on these prototype
Externí odkaz:
http://arxiv.org/abs/2405.04975
Publikováno v:
Zhongguo Jianchuan Yanjiu, Vol 13, Iss S1, Pp 157-164 (2019)
[Objectives] In this paper, the harmonic characteristics of output voltage for a matrix converter (MC)in marine electric propulsion system are studied.[Methods] Based on triple Fourier Series,an analytical calculation method to determine harmonic com
Externí odkaz:
https://doaj.org/article/84a9273042c64f18b771a08a859eebb8
Autor:
Li, Jiazhi, Khayatkhoei, Mahyar, Zhu, Jiageng, Xie, Hanchen, Hussein, Mohamed E., AbdAlmageed, Wael
Ensuring a neural network is not relying on protected attributes (e.g., race, sex, age) for prediction is crucial in advancing fair and trustworthy AI. While several promising methods for removing attribute bias in neural networks have been proposed,
Externí odkaz:
http://arxiv.org/abs/2311.07141
Autor:
Li, Jiazhi, Khayatkhoei, Mahyar, Zhu, Jiageng, Xie, Hanchen, Hussein, Mohamed E., AbdAlmageed, Wael
Ensuring a neural network is not relying on protected attributes (e.g., race, sex, age) for predictions is crucial in advancing fair and trustworthy AI. While several promising methods for removing attribute bias in neural networks have been proposed
Externí odkaz:
http://arxiv.org/abs/2310.04955
Autor:
Zhu, Jiageng, Xie, Hanchen, Wu, Jianhua, Li, Jiazhi, Khayatkhoei, Mahyar, Hussein, Mohamed E., AbdAlmageed, Wael
Discovering causal relations among semantic factors is an emergent topic in representation learning. Most causal representation learning (CRL) methods are fully supervised, which is impractical due to costly labeling. To resolve this restriction, wea
Externí odkaz:
http://arxiv.org/abs/2308.05707
Autor:
Xie, Hanchen, Zhu, Jiageng, Khayatkhoei, Mahyar, Li, Jiazhi, Hussein, Mohamed E., AbdAlmageed, Wael
Dynamics prediction, which is the problem of predicting future states of scene objects based on current and prior states, is drawing increasing attention as an instance of learning physics. To solve this problem, Region Proposal Convolutional Interac
Externí odkaz:
http://arxiv.org/abs/2305.07648
Autor:
Li, Jiazhi, Abd-Almageed, Wael
As the social impact of visual recognition has been under scrutiny, several protected-attribute balanced datasets emerged to address dataset bias in imbalanced datasets. However, in facial attribute classification, dataset bias stems from both protec
Externí odkaz:
http://arxiv.org/abs/2209.06850
Autor:
Li, Jiazhi, Zhou, Tingting, Chen, Yunnong, Chang, Yanfang, Zhen, Yankun, Sun, Lingyun, Chen, Liuqing
While some work attempt to generate front-end code intelligently from UI screenshots, it may be more convenient to utilize UI design drafts in Sketch which is a popular UI design software, because we can access multimodal UI information directly such
Externí odkaz:
http://arxiv.org/abs/2208.06658
Autor:
Li, Jiazhi, Abd-Almageed, Wael
As equality issues in the use of face recognition have garnered a lot of attention lately, greater efforts have been made to debiased deep learning models to improve fairness to minorities. However, there is still no clear definition nor sufficient a
Externí odkaz:
http://arxiv.org/abs/2111.04673