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Denoising of Rician corrupted 3D magnetic resonance images using tensor -SVD
Biomedical Signal Processing and Control, 2018Abstract In this paper, we propose a new method for denoising the volumetric magnetic resonance (MR) images degraded with Rician noise. Taking into account the multi-frame (multi-linear) nature, the proposed method formulates an unsophisticated approach by contemplating the MR data as third order tensor.
Hawazin S. Khaleel +3 more
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Sequential Unfolding SVD for Tensors With Applications in Array Signal Processing
IEEE Transactions on Signal Processing, 2009This paper contributes to the field of higher order (N > 2) tensor decompositions in signal processing. A novel PARATREE tensor model is introduced, accompanied with sequential unfolding SVD (SUSVD) algorithm. SUSVD, as the name indicates, applies a matrix singular value decomposition sequentially on the unfolded tensor reshaped from the right hand ...
J. Salmi, A. Richter, V. Koivunen
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Parallel Tensor Train Rounding using Gram SVD
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2022Hussam Al Daas +2 more
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Parallel convolutional processing using an integrated photonic tensor core
Nature, 2021Johannes Feldmann, Nathan Youngblood
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Tensor lattice field theory for renormalization and quantum computing
Reviews of Modern Physics, 2022Yannick Meurice +2 more
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Third-order nonlinear Hall effect induced by the Berry-connection polarizability tensor
Nature Nanotechnology, 2021Shen Lai, Huiying Liu, Zhaowei Zhang
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Higher-dimensional processing using a photonic tensor core with continuous-time data
Nature Photonics, 2023Bowei Dong +2 more
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Measurement of the quantum geometric tensor and of the anomalous Hall drift
Nature, 2020Antonio Gianfrate +2 more
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Incremental SVD-based Tensor-Train Decomposition for Traffic Flow Data
2023 6th International Conference on Artificial Intelligence and Pattern Recognition (AIPR), 2023Jingbo Sun, Shuangyu Liu, Shengsheng He
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