Zobrazeno 1 - 10
of 695
pro vyhledávání: '"ZHANG, Ruiwen"'
Autor:
Wang, Wei a, b, ∗, Du, Yi a, Datta, Sayantap a, Fowler, Josef F. a, Sang, Hannah T. a, Albadari, Najah c, Li, Wei c, Foster, Jennifer d, Zhang, Ruiwen a, b, ∗∗
Publikováno v:
In Genes & Diseases March 2025 12(2)
Autor:
Zhao, Xueqi, Li, Yingbo, Li, Zhenli, Hu, Dexiang, Zhang, Ruiwen, Li, Mengzhen, Liu, Yaoyang, Xiu, Xiaomeng, Jia, Hongwei, Wang, Hanxun, Liu, Yang, Yang, Huali, Cheng, Maosheng
Publikováno v:
In Bioorganic Chemistry September 2024 150
Autor:
Zhang, Ruiwen, He, Zhou, Shi, Yajing, Sun, Xiangkun, Chen, Xinyu, Wang, Guoquan, Zhang, Yizhou, Gao, Pan, Wu, Ying, Lu, Shuhan, Duan, Junyi, Sun, Shangwu, Yang, Na, Fan, Wei, Zhao, Kaitao, Yang, Bei, Xia, Yuchen, Zhang, Yan, Zhang, Ying, Yin, Hao
Publikováno v:
In Cell 25 July 2024 187(15):3936-3952
Publikováno v:
In Journal of Alloys and Compounds 25 May 2024 985
Autor:
Zhao, Xueqi, Zhang, Ruiwen, Hu, Dexiang, Li, Mengzhen, Liu, Yaoyang, Xiu, Xiaomeng, Jia, Hongwei, Wang, Hanxun, Li, Zhenli, Liu, Yang, Yang, Huali, Cheng, Maosheng
Publikováno v:
In Dyes and Pigments May 2024 224
Publikováno v:
In Chemical Engineering Journal 1 April 2024 485
In a complex road traffic scene, illegal lane intrusion of pedestrians or cyclists constitutes one of the main safety challenges in autonomous driving application. In this paper, we propose a novel object-level phase space reconstruction network (PSR
Externí odkaz:
http://arxiv.org/abs/2102.11149
Publikováno v:
In Mechanical Systems and Signal Processing 15 February 2024 208
Autor:
Liu, Yaoyang, Ma, Chao, Li, Yingbo, Li, Mengzhen, Cui, Tao, Zhao, Xueqi, Li, Zhenli, Jia, Hongwei, Wang, Hanxun, Xiu, Xiaomeng, Hu, Dexiang, Zhang, Ruiwen, Wang, Ningwei, Liu, Peng, Yang, Huali, Cheng, Maosheng
Publikováno v:
In European Journal of Medicinal Chemistry 5 February 2024 265
Publikováno v:
2020,Computer Science & Information Technology (CS & IT)
Graph convolutional networks (GCNs) can effectively capture the features of related nodes and improve the performance of the model. More attention is paid to employing GCN in Skeleton-Based action recognition. But existing methods based on GCNs have
Externí odkaz:
http://arxiv.org/abs/2012.02970