Zobrazeno 1 - 10
of 134
pro vyhledávání: '"YANG Shaokang"'
Publikováno v:
Renmin Zhujiang, Pp 1-11 (2024)
It is of great reference significance for drought recovery and water resources management to explore the response rules of meteorological and hydrological drought characteristics during the drought recovery period. In this study, standardized precipi
Externí odkaz:
https://doaj.org/article/b4146496be9c4bc8809d62117855da7f
Autor:
Yang, Hongjie, Xiao, Yong, Yang, Shaokang, Zhao, Zhen, Wang, Shengbin, Xiao, Shanhu, Wang, Jie, Zhang, Yuqing, Wang, Jianhui, Yuan, Youjin, Wang, Ning, Wang, Liwei, Hu, Wenxu
Publikováno v:
In Journal of Hydrology: Regional Studies December 2024 56
Autor:
Luo, Chongda, Yan, Xintong, Yang, Shaokang, Ren, Sichen, Luo, Yan, Li, Jiazheng, Wang, Ping, Shao, Yunfeng, Li, Wei, Li, Song, Yang, Jingjing, Cao, Ruiyuan, Zhong, Wu
Publikováno v:
In Virologica Sinica October 2024 39(5):802-811
Autor:
He, Ju, Yang, Shuo, Yang, Shaokang, Kortylewski, Adam, Yuan, Xiaoding, Chen, Jie-Neng, Liu, Shuai, Yang, Cheng, Yu, Qihang, Yuille, Alan
It is natural to represent objects in terms of their parts. This has the potential to improve the performance of algorithms for object recognition and segmentation but can also help for downstream tasks like activity recognition. Research on part-bas
Externí odkaz:
http://arxiv.org/abs/2112.00933
Autor:
Zhang, Yida, Ma, Zhentao, Yang, Shaokang, Wang, Qingyu, Liu, Limin, Bai, Yu, Rao, Dewei, Wang, Gongming, Li, Hongliang, Zheng, Xusheng
Publikováno v:
In Science Bulletin 30 April 2024 69(8):1100-1108
Autor:
He, Ju, Kortylewski, Adam, Yang, Shaokang, Liu, Shuai, Yang, Cheng, Wang, Changhu, Yuille, Alan
Semi-Supervised Learning (SSL) has shown its strong ability in utilizing unlabeled data when labeled data is scarce. However, most SSL algorithms work under the assumption that the class distributions are balanced in both training and test sets. In t
Externí odkaz:
http://arxiv.org/abs/2106.00209
Re-rank Coarse Classification with Local Region Enhanced Features for Fine-Grained Image Recognition
Fine-grained image recognition is very challenging due to the difficulty of capturing both semantic global features and discriminative local features. Meanwhile, these two features are not easy to be integrated, which are even conflicting when used s
Externí odkaz:
http://arxiv.org/abs/2102.09875
Akademický článek
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Akademický článek
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Autor:
Chen, Xingjuan, Yan, Yunzheng, Song, Huijuan, Wang, Zhuang, Wang, Apeng, Yang, Jingjing, Zhou, Rui, Xu, Shijie, Yang, Shaokang, Li, Wei, Qin, Xiaoyu, Dai, Qingsong, Liu, Mingliang, Lv, Kai, Cao, Ruiyuan, Zhong, Wu
Publikováno v:
In European Journal of Medicinal Chemistry 5 December 2023 261