Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Hengliang, Zhu"'
Publikováno v:
International Journal of Advanced Computer Science & Applications; Oct2024, Vol. 15 Issue 10, p1052-1061, 10p
Publikováno v:
Mathematics, Vol 10, Iss 21, p 4150 (2022)
Recently, it has been demonstrated that the performance of an object detection network can be improved by embedding an attention module into it. In this work, we propose a lightweight and effective attention mechanism named multibranch attention (M3A
Externí odkaz:
https://doaj.org/article/aaecb70bc73545238926822fd1274ec9
Publikováno v:
IET Computer Vision, Vol 13, Iss 7, Pp 632-639 (2019)
Face alignment has made great progress in recent years and the cascade regression framework is one of the main contributors. However, the performance of this framework is unsatisfactory on heavily occluded faces or those far from the frontal pose. Th
Externí odkaz:
https://doaj.org/article/d586b02cecb843e0af75746c0548d5a0
Publikováno v:
2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9865f42135b056e04e5df915ec3a9ba
https://doi.org/10.1109/ccis57298.2022.10016395
https://doi.org/10.1109/ccis57298.2022.10016395
Publikováno v:
Neurocomputing. 396:477-486
Facial landmarks are highly correlated with each other since a certain landmark can be estimated by its neighboring landmarks. Most of the existing deep learning methods only use one fully-connected layer called shape prediction layer to estimate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff0920ff2b861faadf720a8480f2239d
https://doi.org/10.1016/j.neucom.2018.11.108
https://doi.org/10.1016/j.neucom.2018.11.108
Autor:
Hengliang Zhu, Huajie Cai, Xiaokun Wang, Tao Chen, Chaohui Zhen, Zhenzhan Zhang, Xiaojiao Ruan, Guoxin Li
Publikováno v:
Ann Transl Med
BACKGROUND: Sodium-glucose co-transporter 1 (SGLT1) may play a synergistic role in gluconeogenesis (GNG) and glucagon-like peptide-1 (GLP-1) expression. We proposed the hypothesis of a “SGLT1 bridge” as an indication for “surgical diabetes” t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73ae122fdc16e83e85dba929d4e76903
https://pubmed.ncbi.nlm.nih.gov/35571394
https://pubmed.ncbi.nlm.nih.gov/35571394
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031208645
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ce49a45a562161ab76f0479f504bdde
https://doi.org/10.1007/978-3-031-20865-2_38
https://doi.org/10.1007/978-3-031-20865-2_38
Autor:
Mengke Tian, Hengliang Zhu, Yong Wang, Yimao Cai, Feng Liu, Pengrong Lin, Yingzhuo Huang, Xiaochen Xie
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783031243851
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48ef6e2def68289bf035ac75a2ebf883
https://doi.org/10.1007/978-3-031-24386-8_26
https://doi.org/10.1007/978-3-031-24386-8_26
Publikováno v:
IET Computer Vision. 13:632-639
Face alignment has made great progress in recent years and the cascade regression framework is one of the main contributors. However, the performance of this framework is unsatisfactory on heavily occluded faces or those far from the frontal pose. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e077a641210979fddedae7a8f4cdb33
https://doi.org/10.1049/iet-cvi.2018.5347
https://doi.org/10.1049/iet-cvi.2018.5347
Publikováno v:
Neural Computing and Applications. 32:8507-8516
In this work, instead of designing deeper convolutional neural networks, we investigate the relationship between the nonlinearity of convolution layer and the performance of the network. We modify the normal convolution layer by inserting quadratic c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fb3a3e011920561980838d046992d54
https://doi.org/10.1007/s00521-019-04316-4
https://doi.org/10.1007/s00521-019-04316-4