Results 51 to 60 of about 3,137 (156)
Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition
Remote Sensing, 2021 Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI), aiming to produce a super-resolution hyperspectral image, has recently attracted increasing research interest.
Marzieh Zare +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingDeep learning methodologies have demonstrated considerable effectiveness in hyperspectral anomaly detection (HAD). However, the practicality of deep learning-based HAD in real-world applications is impeded by challenges arising from limited labeled data,
Yulei Wang +4 more
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Multispectral image denoising using sparse and graph Laplacian Tucker decomposition
Computational Visual Media, 2020 Multispectral image denoising is a basic problem whose results affect subsequent processes such as target detection and classification. Numerous approaches have been proposed, but there are still many challenges, particularly in using prior knowledge of ...
Xiaoce Wu +3 more
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Computational Urban ScienceThe spatiotemporal mobility patterns and next location prediction of fake base stations (FBS) provide important technical support for the police to prevent spam messages from FBS.
Yufei·Shi, Haiyan Tao, Li Zhuo
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ULA Blind Identification Combining Tucker Tensor Decomposition and Alternating Least Squares [PDF]
Jisuanji gongcheng, 2017 In order to improve the computational efficiency of Blind Identification(BI) of Uniform Linear Array(ULA) system,an improved ULA BI algorithm is proposed.Firstly,the signal propagation model of ULA system is established.Then,the algebraic structure and ...
HU Dan,GUO Yingjie
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Bearing Fault Diagnosis Based on Multi-Channel WOA-VMD and Tucker Decomposition
Applied SciencesTo address the challenges that rolling bearing vibration signals are easily affected by noise and that traditional single-channel methods cannot fully exploit multi-channel information, this paper proposes a multi-channel fault diagnosis method combining
Lingjiao Chen +6 more
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Non-parallel dictionary learning for voice conversion using non-negative Tucker decomposition
EURASIP Journal on Audio, Speech, and Music Processing, 2019 Voice conversion (VC) is a technique of exclusively converting speaker-specific information in the source speech while preserving the associated phonemic information.
Yuki Takashima +3 more
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Equivariant and Scale-Free Tucker Decomposition Models
Bayesian Analysis, 2016 Analyses of array-valued datasets often involve reduced-rank array approximations, typically obtained via least-squares or truncations of array decompositions. However, least-squares approximations tend to be noisy in high-dimensional settings, and may not be appropriate for arrays that include discrete or ordinal measurements.
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Incremental Hierarchical Tucker Decomposition
We present two new algorithms for approximating and updating the hierarchical Tucker decomposition of tensor streams. The first algorithm, Batch Hierarchical Tucker - leaf to root (BHT-l2r), proposes an alternative and more efficient way of approximating a batch of similar tensors in hierarchical Tucker format. The second algorithm, Hierarchical Tucker
Aksoy, Doruk, Gorodetsky, Alex A.
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Some Theory on Non-negative Tucker Decomposition [PDF]
, 2017 Some theoretical difficulties that arise from dimensionality reduction for tensors with non-negative coefficients is discussed in this paper. A necessary and sufficient condition is derived for a low non-negative rank tensor to admit a non-negative Tucker decomposition with a core of the same non-negative rank.
Jeremy E. Cohen +2 more
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