Results 131 to 140 of about 2,392 (180)

Revealing tissue architecture through the hypercomplex Fourier analysis of spatial transcriptomics data. [PDF]

Bioinform Adv
Frost HR.
europepmc   +1 more source

Diffusion tensor imaging analysis along the perivascular space suggests impaired glymphatic clearance in Lewy body dementia subtypes

Hannaway N, Zarkali A, Bhome R, Dobreva I, Kalam S, Thomas GE, Dymerska B, Gorostiaga Belio I, Tucker K, Heslegrave A, Zetterberg H, Weil RS.   +11 more
europepmc   +1 more source

Identifying novel metabolomics risk factors for lacunar stroke and vascular cognitive impairment

Ng WH, Aghakishiyeva E, Markus HS, Harshfield EL.   +3 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Robust Tensor SVD and Recovery With Rank Estimation

IEEE Transactions on Cybernetics, 2022
Tensor singular value decomposition (t-SVD) has recently become increasingly popular for tensor recovery under partial and/or corrupted observations. However, the existing t -SVD-based methods neither make use of a rank prior nor provide an accurate rank estimation (RE), which would limit their recovery performance.
Qiquan Shi, Yiu-Ming Cheung, Jian Lou
openaire   +2 more sources

Weighted tensor nuclear norm minimization for tensor completion using tensor-SVD

Pattern Recognition Letters, 2020
Abstract In this paper, we consider the tensor completion problem, which aims to estimate missing values from limited information. Our model is based on the recently proposed tensor-SVD, which uses the relationships among the color channels in an image or video recovery problem. To improve the availability of the model, we propose the weighted tensor
Yang Mu, Ping Wang, Liangfu Lu, Xuyun Zhang, Lianyong Qi   +4 more
openaire   +1 more source

Tensor Completion via A Generalized Transformed Tensor T-Product Decomposition Without t-SVD

Journal of Scientific Computing, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hongjin He, Chen Ling, Wenhui Xie
openaire   +2 more sources

Dynamic MRI Reconstruction Using Tensor-SVD

2018 14th IEEE International Conference on Signal Processing (ICSP), 2018
In this paper we propose to reconstruct dynamic magnetic resonance images from highly sparse sampling k-t space data by enhancing the low rankness and sparsity simultaneously. We introduce Tensor Singular Value Decomposition (t-SVD) instead of matrix SVD to maintain the structure of dynamic MR images.
Jianhang Ai, Shuli Ma, Huiqian Du, Liping Fang   +3 more
openaire   +1 more source

SVD-Based Tensor-Completion Technique for Background Initialization

IEEE Transactions on Image Processing, 2018
Extracting the background from a video in the presence of various moving patterns is the focus of several background-initialization approaches. To model the scene background using rank-one matrices, this paper proposes a background-initialization technique that relies on the singular-value decomposition (SVD) of spatiotemporally extracted slices from ...
Ibrahim Kajo, Nidal Kamel, Yassine Ruichek, Aamir Saeed Malik   +3 more
openaire   +2 more sources

Decompositions of third‐order tensors: HOSVD, T‐SVD, and Beyond

Numerical Linear Algebra with Applications, 2020
SummaryThe higher order singular value decomposition, which is regarded as a generalization of the matrix singular value decomposition (SVD), has a long history and is well established, while the T‐SVD is relatively new and lacks systematic analysis. Because of the unusual tensor‐tensor product that the T‐SVD is based on, the form of the T‐SVD may be ...
Chao Zeng, Michael K. Ng
openaire   +2 more sources

Robust low-rank tensor reconstruction using high-order t-SVD

Journal of Electronic Imaging, 2021
Currently, robust low-rank tensor reconstruction based on tensor singular value decomposition (t-SVD) has made remarkable achievements in the fields of computer vision, image processing, etc. However, existing works mainly concentrate on third-order tensors while order-d (d  ≥  4) tensors are commonly encountered in practical applications, such as ...
Wenjin Qin, Hailin Wang, Feng Zhang, Mingwei Dai, Jianjun Wang   +4 more
openaire   +1 more source