Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Fengtao Xiang"'
Publikováno v:
智能科学与技术学报, Vol 5, Pp 51-57 (2023)
Aiming at the problems related to the spread and prevention and control of COVID-19, the COVID-19 epidemic was studied based on agent based modeling thought.Firstly, based on the COVID-19 transmission mechanism, a mathematical model was established o
Externí odkaz:
https://doaj.org/article/5acb9c6e9f674b26904414f9f4c90a2d
Autor:
Fenhong Yang, Yingying Zhu, Xiaohan Li, Fengtao Xiang, Moru Deng, Wei Zhang, Wei Song, Hao Sun, Changbo Tang
Publikováno v:
Foods, Vol 12, Iss 23, p 4225 (2023)
Plant polyphenols with a catechol structure can form covalent adducts with meat proteins, which affects the quality and processing of meat products. However, there is a lack of fast and effective methods of characterizing these adducts and understand
Externí odkaz:
https://doaj.org/article/39ac2fc9a4b04eb0b426e5ae99ca20f0
Publikováno v:
IEEE Access, Vol 7, Pp 142738-142749 (2019)
Hexagonal grids use a hierarchical subdivision tessellation to cover the entire plane or sphere. Due to the 6-fold rotational symmetry, hexagonal grids have some advantages (e.g. isoperimetry, equidistant neighbors, and uniform connectivity) over qua
Externí odkaz:
https://doaj.org/article/23fc366025d24ec69b420d557dabb543
Publikováno v:
Applied Sciences, Vol 11, Iss 21, p 10479 (2021)
The adversarial samples threaten the effectiveness of machine learning (ML) models and algorithms in many applications. In particular, black-box attack methods are quite close to actual scenarios. Research on black-box attack methods and the generati
Externí odkaz:
https://doaj.org/article/31fcb370a0354069ae9989ccb021af4e
Publikováno v:
Electronics; Volume 11; Issue 6; Pages: 896
In this paper, more efficient allocation of forces is analyzed in the future air confrontation among unmanned aerial vehicle swarms. A novel method is proposed for swarm confrontation based on the Lanchester law and Nash equilibrium. Due to the huge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66a9f6462d44a2efea3089212a7667c2
Autor:
Ye Yuan, Jian Liu, Peng Zhao, Wei Wang, Xiao Gu, Yi Rong, Tinggeng Lai, Yuze Chen, Kuankuan Xin, Xin Niu, Fengtao Xiang, Hong Huo, Zhaoyu Li, Tao Fang
Publikováno v:
Journal of neural engineering. 19(3)
Objective. Reconstruction of connectomes at the cellular scale is a prerequisite for understanding the principles of neural circuits. However, due to methodological limits, scientists have reconstructed the connectomes of only a few organisms such as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::513b044523b708d8fa65448a71a2243b
https://pubmed.ncbi.nlm.nih.gov/35462357
https://pubmed.ncbi.nlm.nih.gov/35462357
Publikováno v:
Applied Sciences
Volume 11
Issue 21
Applied Sciences, Vol 11, Iss 10479, p 10479 (2021)
Volume 11
Issue 21
Applied Sciences, Vol 11, Iss 10479, p 10479 (2021)
The adversarial samples threaten the effectiveness of machine learning (ML) models and algorithms in many applications. In particular, black-box attack methods are quite close to actual scenarios. Research on black-box attack methods and the generati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c895e5afd3be016df95d93cd0e7e3cc
Publikováno v:
2021 China Automation Congress (CAC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c44c18ef727ce379b2efad4479626923
https://doi.org/10.1109/cac53003.2021.9728272
https://doi.org/10.1109/cac53003.2021.9728272
Publikováno v:
2021 China Automation Congress (CAC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb6e11c8907610e6ca39c2d173f7aa7e
https://doi.org/10.1109/cac53003.2021.9727882
https://doi.org/10.1109/cac53003.2021.9727882
Publikováno v:
RCAR
In image classification tasks, the training of deep convolutional neural networks generally requires a large amount of data, and due to the constraints of environment, resources and time, it is of great practical importance to use fewer training samp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0bff4ae90866e8ff7a7ec7e9a69cdb6
https://doi.org/10.1109/rcar52367.2021.9517519
https://doi.org/10.1109/rcar52367.2021.9517519