Results 101 to 110 of about 249,242 (319)

Multi-View Tensor Sparse Representation Model for SAR Target Recognition

IEEE Access, 2019
The local structure feature of the target in synthetic aperture radar (SAR) image and the inner correlation among multiple SAR images of the same target can effectively improve the recognition performance.
Zhiqiang He, Huaitie Xiao, Zhuangzhuang Tian   +2 more
doaj   +1 more source

M-Tensors and Nonsingular M-Tensors

, 2013
The M-matrix is an important concept in matrix theory, and has many applications. Recently, this concept has been extended to higher order tensors [18]. In this paper, we establish some important properties of M-tensors and nonsingular M-tensors. An M-tensor is a Z-tensor.
Ding, Weiyang, Qi, Liqun, Wei, Yimin
openaire   +2 more sources

Implementation of anatomical navigators for real time motion correction in diffusion tensor imaging

, 2012
Includes bibliographical references.Prospective motion correction methods using an optical system, diffusion-weighted prospective acquisition correction, or a free induction decay navigator have recently been applied to correct for motion in diffusion ...
Alhamud, Alkathafi Ali
core  

Evaluating Energy Absorption Performance of Filled Lattice Structures

Advanced Engineering Materials, EarlyView.
Maximum stress must be considered to robustly evaluate energy absorber designs. This approach was applied to compare all types of absorbers in a single Ashby diagram and determine the utility of filling lattice voids with a second material. High‐performance fillers can improve the performance of lattices that are limited by buckling or catastrophic ...
Christian Bonney, William P. King, Iwona Jasiuk   +2 more
wiley   +1 more source

Correcting variance and polarity indeterminacies of extracted components by canonical polyadic decomposition

Brain-Apparatus Communication
Background Back-projection has been used to correct the variance and polarity indeterminacies for the independent component analysis. The variance and polarity of the components are essential features of neuroscience studies.Objective This work extends ...
Yuxing Hao, Huanjie Li, Guoqiang Hu, Wei Zhao, Fengyu Cong   +4 more
doaj   +1 more source

Classification of Multi-Frequency Polarimetric SAR Images Based on Multi-Linear Subspace Learning of Tensor Objects

Remote Sensing, 2015
One key problem for the classification of multi-frequency polarimetric SAR images is to extract target features simultaneously in the aspects of frequency, polarization and spatial texture.
Chun Liu, Junjun Yin, Jian Yang, Wei Gao
doaj   +1 more source

Computational and Statistical Guarantees for Tensor-on-Tensor Regression With Tensor Train Decomposition

IEEE Transactions on Pattern Analysis and Machine Intelligence
arXiv admin note: text overlap with arXiv:2401 ...
Zhen Qin, Zhihui Zhu
openaire   +3 more sources

Stability effects on results of diffusion tensor imaging analysis by reduction of the number of gradient directions due to motion artifacts: an application to presymptomatic Huntington's disease.

, 2011
In diffusion tensor imaging (DTI), an improvement in the signal-to-noise ratio (SNR) of the fractional anisotropy (FA) maps can be obtained when the number of recorded gradient directions (GD) is increased.
Müller, HP, Kassubek, J, Landwehrmeyer, GB, Kloppel, S, Tabrizi, SJ, Süssmuth, SD, Ludolph, A   +6 more
core  

Rafting of Ni‐Based Superalloys Under Multiaxial Load as Understood by Phase‐Field Simulations and Critical Experiments

Advanced Engineering Materials, EarlyView.
Phase‐field simulations coupled with dislocation‐density‐based crystal plasticity modeling reproduce γ′ rafting behavior in single‐crystal Ni‐based superalloys under varied loading conditions. The model captures both macroscopic creep and microscopic morphology evolution, with results matching high‐temperature creep experiments.
Micheal Younan, David Bürger, Gunther Eggeler, Oleg Shchyglo, Ingo Steinbach, Muhammad Adil Ali   +5 more
wiley   +1 more source

Enhanced Multilinear PCA for Efficient Image Analysis and Dimensionality Reduction: Unlocking the Potential of Complex Image Data

Mathematics
This paper presents an Enhanced Multilinear Principal Component Analysis (EMPCA) algorithm, an improved variant of the traditional Multilinear Principal Component Analysis (MPCA) tailored for efficient dimensionality reduction in high-dimensional data ...
Tianyu Sun, Lang He, Xi Fang, Liang Xie
doaj   +1 more source