Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Kuang Zhou"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Fine-grained management of rice fields can enhance the yield and quality of rice crops. Challenges in achieving fine classification include interference from similar vegetation, the irregularity of natural field shapes, and complex scale var
Externí odkaz:
https://doaj.org/article/7a1a7e8040094c1d89b1f22047bafb0a
Publikováno v:
Entropy, Vol 23, Iss 2, p 206 (2021)
Entropy measures the uncertainty associated with a random variable. It has important applications in cybernetics, probability theory, astrophysics, life sciences and other fields. Recently, many authors focused on the estimation of entropy with diffe
Externí odkaz:
https://doaj.org/article/275d629cd1384a36b8c20f6e621745c0
Autor:
Kuang Zhou, Yimin Shi
Publikováno v:
Entropy, Vol 22, Iss 10, p 1106 (2020)
In this paper, the evidential estimation method for the parameters of the mixed exponential distribution is considered when a sample is obtained from Type-II progressively censored data. Different from the traditional statistical inference methods fo
Externí odkaz:
https://doaj.org/article/8bcf5ff087b04b89879961c8e7581859
Publikováno v:
IEEE Transactions on Mobile Computing. 22:634-646
With the increasing prominence of smart mobile devices, an innovative distributed computing paradigm, namely Mobile Crowdsourcing (MCS), has emerged. By directly recruiting skilled workers, MCS exploits the power of the crowd to complete location-dep
Autor:
null Huiling Wang, Jingjing Wang, Zhen Teng, Wei Fan, Pengfei Deng, Zhenyu Wen, Kuang Zhou, Xiaoniu Xu
Publikováno v:
Eurasian Soil Science. 55:425-436
Publikováno v:
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning, 2022, 151, pp.322-343. ⟨10.1016/j.ijar.2022.10.001⟩
International Journal of Approximate Reasoning, 2022, 151, pp.322-343. ⟨10.1016/j.ijar.2022.10.001⟩
International audience; In some real clustering tasks, the data may be sparse and uncertain. Although there is usually some useful knowledge in related scenes, the data among different domains is often of great inconsistency. A new unsupervised trans
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::841d38a688354546ef06eb38e49f4fd4
https://hal.science/hal-03991668/document
https://hal.science/hal-03991668/document
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2021, 32 (5), pp.2015-2029. ⟨10.1109/TNNLS.2020.2995862⟩
IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2021, 32 (5), pp.2015-2029. ⟨10.1109/TNNLS.2020.2995862⟩
International audience; In applications of domain adaptation, there may exist multiple source domains, which can provide more or less complementary knowledge for pattern classification in the target domain. In order to improve the classification accu
Publikováno v:
Reliability Engineering & System Safety. 231:108976
Autor:
Kuang Zhou, Ming Jiang
Publikováno v:
Belief Functions: Theory and Applications ISBN: 9783031178009
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9c8ef8bc01a9bd818b6a3fc14d3ea81
https://doi.org/10.1007/978-3-031-17801-6_2
https://doi.org/10.1007/978-3-031-17801-6_2
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, pp.1-13. ⟨10.1109/TSMC.2022.3205365⟩
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, pp.1-13. ⟨10.1109/TSMC.2022.3205365⟩
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ce97148e0163f5f189516b3ad494976
https://hal.science/hal-03816204/document
https://hal.science/hal-03816204/document