Zobrazeno 1 - 10
of 946
pro vyhledávání: '"Tai Xiang"'
Publikováno v:
Journal of Ophthalmology, Vol 2024 (2024)
Introduction. To evaluate the changes of lens antidilatation, antiedema, and antienzymolysis ability after different concentrations of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and N-hydroxysuccinimide (EDC-NHS)-induced collagen cross-linking. M
Externí odkaz:
https://doaj.org/article/72d64e638d9145cea7a0b1f66d1a03f7
In this paper, the quaternion matrix UTV (QUTV) decomposition and quaternion tensor UTV (QTUTV) decomposition are proposed. To begin, the terms QUTV and QTUTV are defined, followed by the algorithms. Subsequently, by employing random sampling from th
Externí odkaz:
http://arxiv.org/abs/2406.05734
Publikováno v:
In Applied Mathematical Modelling February 2025 138 Part A
The convolution operation is a powerful tool for feature extraction and plays a prominent role in the field of computer vision. However, when targeting the pixel-wise tasks like image fusion, it would not fully perceive the particularity of each pixe
Externí odkaz:
http://arxiv.org/abs/2107.11617
Autor:
Si-Si Yang, Wen-Chang Huang, Peng Wang, Fang-Qi Gong, Tai-Xiang Liu, Jin-Fa Tou, Deng-Ming Lai
Publikováno v:
BMC Pediatrics, Vol 23, Iss 1, Pp 1-6 (2023)
Abstract Purpose The purpose of this study was to explore echocardiographic parameters of the left ventricle (LV) in relation to the outcomes of omphalocele neonates with pulmonary hypertension (PH). Methods This retrospective study was conducted amo
Externí odkaz:
https://doaj.org/article/f4e10dc9d47b4a2095f9a28b1c8a8c79
In this paper, we study multi-dimensional image recovery. Recently, transform-based tensor nuclear norm minimization methods are considered to capture low-rank tensor structures to recover third-order tensors in multi-dimensional image processing app
Externí odkaz:
http://arxiv.org/abs/2105.14320
Publikováno v:
In Signal Processing February 2024 215
Publikováno v:
In Journal of Computational and Applied Mathematics 15 January 2024 436
In this paper, we propose a novel tensor learning and coding model for third-order data completion. Our model is to learn a data-adaptive dictionary from the given observations, and determine the coding coefficients of third-order tensor tubes. In th
Externí odkaz:
http://arxiv.org/abs/2009.12507
In this paper, we develop a new alternating projection method to compute nonnegative low rank matrix approximation for nonnegative matrices. In the nonnegative low rank matrix approximation method, the projection onto the manifold of fixed rank matri
Externí odkaz:
http://arxiv.org/abs/2009.03998