Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Shuhao SHI"'
Autor:
Tongxian Chen, Xiaoling Zhou, Ruonan Feng, Shuhao Shi, Xiyu Chen, Bingqi Wei, Zhong Hu, Tao Peng
Publikováno v:
BMC Biology, Vol 22, Iss 1, Pp 1-12 (2024)
Abstract NorR, as a single-target regulator, has been demonstrated to be involved in NO detoxification in bacteria under anaerobic conditions. Here, the norR gene was identified and deleted in the genome of Vibrio alginolyticus. The results showed th
Externí odkaz:
https://doaj.org/article/a2995292f41b4e29aed5712fbd832634
Autor:
Shuhao Shi, Jian Chen, Zhengyan Wang, Yuxin Zhang, Yongmao Zhang, Chengqi Fu, Kai Qiao, Bin Yan
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-13 (2024)
Abstract Ensemble learning has the potential to enhance the efficacy of feeble classifiers significantly and is increasingly being utilized in Twitter bot detection. Previous methods have utilized stacking techniques to train the primary classifiers,
Externí odkaz:
https://doaj.org/article/5295f2ffc1eb431a9bc0a288ca70c28f
Publikováno v:
Jin'gangshi yu moliao moju gongcheng, Vol 44, Iss 1, Pp 22-30 (2024)
Low carbon economy and the green economy represent the strategic direction of sustainable development. In order to reduce the manufacturing cost and energy consumption of diamond grinding tools, the preparation process of high-performance vitrified b
Externí odkaz:
https://doaj.org/article/7f6e67093d2849be9fc062e875afd147
Publikováno v:
IET Image Processing, Vol 17, Iss 13, Pp 3688-3701 (2023)
Abstract Element detection is a key step in non‐destructive testing of printed circuit board (PCB) based on computed tomography (CT). In recent years, some image segmentation methods based on deep learning have shown great potential in the element
Externí odkaz:
https://doaj.org/article/f37262fb89fe4d10bfd7c5774e489e8f
Autor:
Shuai Yang, Kai Qiao, Ruoxi Qin, Pengfei Xie, Shuhao Shi, Ningning Liang, Linyuan Wang, Jian Chen, Guoen Hu, Bin Yan
Publikováno v:
Frontiers in Neurorobotics, Vol 15 (2022)
With the continuous development of deep-learning technology, ever more advanced face-swapping methods are being proposed. Recently, face-swapping methods based on generative adversarial networks (GANs) have realized many-to-many face exchanges with f
Externí odkaz:
https://doaj.org/article/b5621be2a019478aa2bcd26b823855a9
Autor:
Pengfei Xie, Shuhao Shi, Shuai Yang, Kai Qiao, Ningning Liang, Linyuan Wang, Jian Chen, Guoen Hu, Bin Yan
Publikováno v:
Frontiers in Neurorobotics, Vol 15 (2021)
Deep neural networks (DNNs) are proven vulnerable to attack against adversarial examples. Black-box transfer attacks pose a massive threat to AI applications without accessing target models. At present, the most effective black-box attack methods mai
Externí odkaz:
https://doaj.org/article/7a9a399a89c84dc597af79f523cd821c
Publikováno v:
Frontiers in Neurorobotics, Vol 15 (2021)
The graph neural network (GNN) has been widely used for graph data representation. However, the existing researches only consider the ideal balanced dataset, and the imbalanced dataset is rarely considered. Traditional methods such as resampling, rew
Externí odkaz:
https://doaj.org/article/3ff80d444be64e5e98263f0fcbf7e9e3
Autor:
Shuhao Shi, Qian Du, Ming Hou, Xiaolei Ye, Li Yang, Shenghui Guo, Jianhong Yi, Ullah Ehsan, Hongbo Zeng
Publikováno v:
Journal of Environmental Sciences. 138:112-120
Autor:
Martin R. Graf, Shruti Apte, Esteban Terzo, Simran Padhye, Shuhao Shi, Megan K. Cox, Roger B. Clark, Vijay Modur, Vasudeo Badarinarayana
Publikováno v:
Journal of Molecular Medicine. 101:375-385
Autor:
Esteban Terzo, Shruti A Apte, Simran Padhye, Saleh Rashed, Wesley Austin, Michael Caponegro, Anupama Reddy, Shuhao Shi, Christy Wang, Roger B Clark, David Sidransky, Vijay Modur, Vasudeo Badarinarayana
Publikováno v:
Cancer Research Communications.
Ribosomes in cancer cells accumulate numerous patient-specific structural and functional modifications that facilitate tumor progression by modifying protein translation. We have taken a unique synthetic chemistry approach to generate novel macrolide