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pro vyhledávání: '"zhang, Hongbing"'
Autor:
Zhang, Hongbing
Low-rank tensor completion (LRTC) aims to recover a complete low-rank tensor from incomplete observed tensor, attracting extensive attention in various practical applications such as image processing and computer vision. However, current methods ofte
Externí odkaz:
http://arxiv.org/abs/2309.16208
Non-convex relaxation methods have been widely used in tensor recovery problems, and compared with convex relaxation methods, can achieve better recovery results. In this paper, a new non-convex function, Minimax Logarithmic Concave Penalty (MLCP) fu
Externí odkaz:
http://arxiv.org/abs/2206.13506
Autor:
Zhou, Julie Xia, Li, Linda Xiaoyan, Zhang, Hongbing, Agborbesong, Ewud, Harris, Peter C., Calvet, James P., Li, Xiaogang
Publikováno v:
In Kidney International August 2024 106(2):258-272
Low-rank tensor completion (LRTC) is an important problem in computer vision and machine learning. The minimax-concave penalty (MCP) function as a non-convex relaxation has achieved good results in the LRTC problem. To makes all the constant paramete
Externí odkaz:
http://arxiv.org/abs/2201.12709
Autor:
XU Shouwu, ZHANG Hongbing, WANG Jingqi, ZHANG Kaili, DOU Lili, GONG Daming, LU Guiwu, QIU Ping
Publikováno v:
Cailiao Baohu, Vol 56, Iss 12, Pp 58-64 (2023)
For improving the photogenerated cathodic protection performance of TiO2 on 304 stainless steel, TiO2 nanobelts were prepared on the surface of Ti sheet by anodization, TiO2/Au films were prepared by ion sputtering, and finally the Z-type heterojunct
Externí odkaz:
https://doaj.org/article/97e6648f75074c5a95beae4dcd88a461
Publikováno v:
In Pattern Recognition December 2024 156
Tensor sparse modeling as a promising approach, in the whole of science and engineering has been a huge success. As is known to all, various data in practical application are often generated by multiple factors, so the use of tensors to represent the
Externí odkaz:
http://arxiv.org/abs/2109.12257
Physics-informed neural networks (PINNs) show great advantages in solving partial differential equations. In this paper, we for the first time propose to study conformable time fractional diffusion equations by using PINNs. By solving the supervise l
Externí odkaz:
http://arxiv.org/abs/2108.07490
The low rank tensor completion (LRTC) problem has attracted great attention in computer vision and signal processing. How to acquire high quality image recovery effect is still an urgent task to be solved at present. This paper proposes a new tensor
Externí odkaz:
http://arxiv.org/abs/2108.03002
Publikováno v:
In Engineering Applications of Artificial Intelligence July 2024 133 Part F