Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Yaoyao Zhong"'
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
BackgroundThe mechanisms underlying central fatigue (CF) induced by high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) are still not fully understood.MethodsIn order to explore the effects of these exercises on
Externí odkaz:
https://doaj.org/article/4490cc2e54f44e0aad9c269ed506f403
Publikováno v:
Pharmaceutical Biology, Vol 60, Iss 1, Pp 801-809 (2022)
Context Due to the resistance of Helicobacter pylori to antibiotics, it is difficult to eradicate this pathogenic bacterium from the host. The role of 1α, 25-dihydroxyvitamin D3 (1,25-D3) in H. pylori-infected gastric mucosa epithelial cells remains
Externí odkaz:
https://doaj.org/article/4595fde4ae894896bb0eb580a0b56643
Autor:
Lihua Wang, Zheng Zhu, Qi Liang, Yecheng Tao, Gaowei Jin, Yaoyao Zhong, Jichen Dai, Ruixia Dai, Zhixiang Wang, Junbo Chen, Lingjie Zhou, Shouyu Ke, Bin Zheng, Linhua Lan, Xiaokun Lin, Tongke Chen
Publikováno v:
Journal of Translational Medicine, Vol 20, Iss 1, Pp 1-19 (2022)
Abstract Background Liver cancer is the fifth leading cause of cancer death worldwide, but early diagnosis and treatment of liver cancer remains a clinical challenge. How to screen and diagnose liver cancer early and prolong the survival rate is stil
Externí odkaz:
https://doaj.org/article/3b039187b7394c83a36cf2c133443db8
Publikováno v:
Frontiers in Psychology, Vol 13 (2023)
The influence of feedback on performance is a topic of ongoing debate, with some previous studies finding it to be ineffective, while others have discovered that it can be helpful or harmful. One possible reason for these inconsistent results may be
Externí odkaz:
https://doaj.org/article/ce470720c6b344879317cb4f1ee52364
Publikováno v:
IEEE Access, Vol 7, Pp 14653-14670 (2019)
Face alignment is a crucial step in face recognition. Through making the position of face consistent, face alignment reduces intra-class variability due to factors such as lighting, background, pose, and perspective transformation, and further facili
Externí odkaz:
https://doaj.org/article/bfae9b66ebfb431abb078e9e26144fc7
Publikováno v:
IEEE Transactions on Multimedia. 24:1186-1197
Learning with noise is a practically challenging problem in deep face recognition. Despite the success of large margin softmax loss functions, these methods are designed for clean face databases. Considering the inevitable noise in the large scale da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e832292a0281071c811f9842d8ed0593
https://doi.org/10.1109/tmm.2021.3123478
https://doi.org/10.1109/tmm.2021.3123478
Publikováno v:
IEEE Transactions on Image Processing. 30:2587-2598
Deep face recognition has achieved great success due to large-scale training databases and rapidly developing loss functions. The existing algorithms devote to realizing an ideal idea: minimizing the intra-class distance and maximizing the inter-clas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44cdf0b41c93d358e7d5200d0b24a720
https://doi.org/10.1109/tip.2020.3048632
https://doi.org/10.1109/tip.2020.3048632
Autor:
Yaoyao Zhong, Weihong Deng
While convenient in daily life, face recognition technologies also raise privacy concerns for regular users on the social media since they could be used to analyze face images and videos, efficiently and surreptitiously without any security restricti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9cd2ec9d90d37bffeff24520cc156445
Publikováno v:
Biometric Recognition ISBN: 9783031202322
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8184f94f8654f8d08c5d3ff0423bec7e
https://doi.org/10.1007/978-3-031-20233-9_18
https://doi.org/10.1007/978-3-031-20233-9_18
Autor:
Yaoyao Zhong, Zhilei Ye
Publikováno v:
Advances in Social Science, Education and Humanities Research.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c49fca168aa3ef9565219733d8622f6a
https://doi.org/10.2991/assehr.k.220504.202
https://doi.org/10.2991/assehr.k.220504.202