High‐resolution dynamic 31P‐MRSI using a low‐rank tensor model
Sign Up to like & getrecommendations! Published in 2017 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.26762
Abstract: To develop a rapid 31P‐MRSI method with high spatiospectral resolution using low‐rank tensor‐based data acquisition and image reconstruction. read more here.
Keywords: resolution; low rank; rank tensor; using low ... See more keywords
On the largeNlimit of Schwinger-Dyson equations of a rank-3 tensor field theory
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Mathematical Physics"
DOI: 10.1063/1.5080306
Abstract: We analyze in this paper the large N limit of the Schwinger-Dyson equations in a rank-3 tensor quantum field theory, which are derived with the help of Ward-Takahashi identities. In order to have a well-defined… read more here.
Keywords: dyson equations; rank tensor; field theory; equations rank ... See more keywords
Low-Rank Tensor Completion by Sum of Tensor Nuclear Norm Minimization
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DOI: 10.1109/access.2019.2940664
Abstract: In this paper, we study the problem of low-rank tensor completion with the purpose of recovering a low-rank tensor from a tensor with partial observed items. To date, there are several different definitions of tensor… read more here.
Keywords: tensor; tensor nuclear; norm minimization; rank tensor ... See more keywords
Nonconvex Low Tubal Rank Tensor Minimization
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2956115
Abstract: In the sparse vector recovery problem, the $L_{0}$ -norm can be approximated by a convex function or a nonconvex function to achieve sparse solutions. In the low-rank matrix recovery problem, the nonconvex matrix rank can… read more here.
Keywords: function; tensor; rank; rank tensor ... See more keywords
Low-Rank Tensor Optimization With Nonlocal Plug-and-Play Regularizers for Snapshot Compressive Imaging
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3136217
Abstract: The increasing volume of hyperspectral images (HSIs) brings great challenges to storage and transmission. Recently, snapshot compressive imaging (SCI), which compresses 3-D HSIs into 2-D measurements, has received increasing attention. Since the original HSIs can… read more here.
Keywords: rank tensor; tensor; hsis; low rank ... See more keywords
Hyperspectral Image Restoration via Subspace-Based Nonlocal Low-Rank Tensor Approximation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3141801
Abstract: In this letter, we present a subspace-based nonlocal low-rank tensor approximation framework (SNLRTA) for hyperspectral image (HSI) restoration. The proposed method consists of a subspace learning method to achieve an accurate subspace characterization of HSI… read more here.
Keywords: rank tensor; tensor approximation; low rank; subspace ... See more keywords
Graph Regularized Low-Rank Tensor-Train for Robust Principal Component Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3170251
Abstract: With the advance of sensor technology, it is becoming more commonplace to collect multi-mode data, i.e., tensors, with high dimensionality. To deal with the large amounts of redundancy in tensorial data, different dimensionality reduction methods… read more here.
Keywords: rank tensor; tensor; low rank; geometry ... See more keywords
Low CP Rank and Tucker Rank Tensor Completion for Estimating Missing Components in Image Data
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2019.2901311
Abstract: Tensor completion recovers missing components of multi-way data. The existing methods use either the Tucker rank or the CANDECOMP/PARAFAC (CP) rank in low-rank tensor optimization for data completion. In fact, these two kinds of tensor… read more here.
Keywords: tucker rank; tensor; completion; low rank ... See more keywords
Hyperspectral Restoration and Fusion With Multispectral Imagery via Low-Rank Tensor-Approximation
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DOI: 10.1109/tgrs.2020.3049014
Abstract: Tensor-based fusion that couples the high spatial resolution of a multispectral image (MSI) to the high spectral resolution of a hyperspectral image (HSI) is considered. The fusion problem is first formulated mathematically as a convex… read more here.
Keywords: tensor; fusion; low rank; tensor approximation ... See more keywords
Efficient Tensor Completion Methods for 5-D Seismic Data Reconstruction: Low-Rank Tensor Train and Tensor Ring
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3179275
Abstract: Five-dimensional seismic reconstruction is receiving increasing attention and can be viewed as a tensor completion problem, which involves reconstructing a low-rank tensor from a partially observed tensor. Tensor train (TT) decomposition and tensor ring (TR)… read more here.
Keywords: rank tensor; tensor; low rank; tensor completion ... See more keywords
Novel Hybrid Low-Rank Tensor Approximation for Hyperspectral Image Mixed Denoising Based on Global-Guided-Nonlocal Prior Mechanism
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3217051
Abstract: Hyperspectral image (HSI) mixed denoising is a challenging task in the fields of remote sensing, environmental monitoring, mineral exploration, and so on. A crucial difficulty is to acquire clean restoration from HSIs that encounter Gaussian… read more here.
Keywords: rank tensor; nonlocal prior; tensor approximation; low rank ... See more keywords