Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Donglin Tan"'
Autor:
Donglin Tan, Xinman Du, Jingyun Tang, Humin Liu, Meng Li, Jianxun Kang, Xiaochun Li, Ying Li, Yue Luo, Qing Wang, Xiaobo Gu, Zonghan Zhao, Xuemei Fu, Xue Chen
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract Blood transfusions from convalescent Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected patients could be used to treat patients with severe infections or immunocompromised patients. However, it is necessary to select the
Externí odkaz:
https://doaj.org/article/d6177e77c7b441149ead013a9b232627
Autor:
Donglin Tan, Junfeng Wang
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-18 (2024)
Abstract In this paper, a novel algorithm is presented for warhead recognition in the defense of ballistic missiles. The range profiles from the warheads of interest in typical illumination directions form a dataset. First, each range profile in the
Externí odkaz:
https://doaj.org/article/06d4eb40f6d9429987a47d8ba78b6af4
Autor:
Jingyun Tang, Humin Liu, Qing Wang, Xiaobo Gu, Jia Wang, Wenjun Li, Yinglan Luo, Yan Li, Lan Deng, Yue Luo, Xinman Du, Donglin Tan, Xuemei Fu, Xue Chen
Publikováno v:
Frontiers in Immunology, Vol 14 (2023)
Externí odkaz:
https://doaj.org/article/2d6029c255e64c32960497fe1a979230
Autor:
Jingyun Tang, Humin Liu, Qing Wang, Xiaobo Gu, Jia Wang, Wenjun Li, Yinglan Luo, Yan Li, Lan Deng, Yue Luo, Xinman Du, Donglin Tan, Xuemei Fu, Xue Chen
Publikováno v:
Frontiers in Immunology, Vol 14 (2023)
BackgroundDemographic information has been shown to help predict high antibody titers of COVID-19 convalescent plasma (CCP) in CCP donors. However, there is no research on the Chinese population and little evidence on whole-blood donors. Therefore, w
Externí odkaz:
https://doaj.org/article/2fe05a29b6f34e51b11dad9bcd565caa
Autor:
Chenxi Li, Zaiying Ma, Liuyue Wang, Weijian Yu, Donglin Tan, Bingbo Gao, Quanlong Feng, Hao Guo, Yuanyuan Zhao
Publikováno v:
Remote Sensing, Vol 13, Iss 22, p 4594 (2021)
High-quality training samples are essential for accurate land cover classification. Due to the difficulties in collecting a large number of training samples, it is of great significance to collect a high-quality sample dataset with a limited sample s
Externí odkaz:
https://doaj.org/article/b0bc70df5eb945b388d9c44cf78368d3
Autor:
Jingyun Tang, Humin Liu, Qing Wang, Xiaobo Gu, Jia Wang, Wenjun Li, Yinglan Luo, Yan Li, Lan Deng, Yue Luo, Xinman Du, Donglin Tan, Xuemei Fu, Xue Chen
Publikováno v:
Frontiers in Immunology; 2023, p1-8, 8p
Autor:
Donglin Tan, Junfeng Wang
Publikováno v:
2021 CIE International Conference on Radar (Radar).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d21bf638776529651f3195b1b855bedc
https://doi.org/10.1109/radar53847.2021.10027903
https://doi.org/10.1109/radar53847.2021.10027903
Autor:
Quanlong Feng, Yuanyuan Zhao, Weijian Yu, Liuyue Wang, Zaiying Ma, Hao Guo, Bingbo Gao, Donglin Tan, Chenxi Li
Publikováno v:
Remote Sensing
Volume 13
Issue 22
Pages: 4594
Remote Sensing, Vol 13, Iss 4594, p 4594 (2021)
Volume 13
Issue 22
Pages: 4594
Remote Sensing, Vol 13, Iss 4594, p 4594 (2021)
High-quality training samples are essential for accurate land cover classification. Due to the difficulties in collecting a large number of training samples, it is of great significance to collect a high-quality sample dataset with a limited sample s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e99f8a3fe61386039c05377f3a63a74e
Autor:
Donglin Tan, Junfeng Wang
Publikováno v:
IGARSS
A novel algorithm is presented for warhead recognition in the defense of ballistic missiles. The deviation of a range profile from a standard range profile is measured by the 2-norm of the difference between the two range profiles. A target is recogn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d3bb977d7771460e203753099a78743
https://doi.org/10.1109/igarss47720.2021.9554832
https://doi.org/10.1109/igarss47720.2021.9554832