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MODULO: A software for Multiscale Proper Orthogonal Decomposition of data
SoftwareX, 2020 In the era of the Big Data revolution, methods for the automatic discovery of regularities in large datasets are becoming essential tools in applied sciences. This article presents an open software package, named MODULO (MODal mULtiscale pOd), to perform
Davide Ninni, Miguel A. Mendez
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Rolling Bearing Fault Diagnosis Based on VMD-MPE and PSO-SVM
Entropy, 2021 The goal of the paper is to present a solution to improve the fault detection accuracy of rolling bearings. The method is based on variational mode decomposition (VMD), multiscale permutation entropy (MPE) and the particle swarm optimization-based ...
Maoyou Ye, Xiaoan Yan, Minping Jia
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An Efficient Algorithm to Highlight Details in Infrared and Visible Image Fusion
IEEE Access, 2021 To improve the fusion quality of infrared and visible images and highlight target and scene details, in this paper, a novel infrared and visible image fusion algorithm is proposed.
Peijin Liu +3 more
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EPT: An R package for ensemble patch transform
SoftwareX, 2021 The primary focus of multiscale analysis is to interpret the temporal characteristics of one-dimensional signals and local spatial patterns of two-dimensional images according to the scale variability.
Donghoh Kim, Hee-Seok Oh, Guebin Choi
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Infrared and visible image fusion via octave Gaussian pyramid framework
Scientific Reports, 2021 Image fusion integrates information from multiple images (of the same scene) to generate a (more informative) composite image suitable for human and computer vision perception.
Lei Yan +6 more
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Multiscale Analysis of Runoff Complexity in the Yanhe Watershed
Entropy, 2022 Runoff complexity is an important indicator reflecting the sustainability of a watershed ecosystem. In order to explore the multiscale characteristics of runoff complexity and analyze its variation and influencing factors in the Yanhe watershed in China ...
Xintong Liu, Hongrui Zhao
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Contrast-Independent, Partially-Explicit Time Discretizations for Nonlinear Multiscale Problems
Mathematics, 2021 This work continues a line of work on developing partially explicit methods for multiscale problems. In our previous works, we considered linear multiscale problems where the spatial heterogeneities are at the subgrid level and are not resolved. In these
Eric T. Chung +3 more
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Sensors, 2021 We propose a novel fault-diagnosis approach for rolling bearings by integrating variational mode decomposition (VMD), refined composite multiscale dispersion entropy (RCMDE), and support vector machine (SVM) optimized by a sparrow search algorithm (SSA).
Jie Lv +3 more
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Fusion of Panchromatic and Multispectral Images Using Multiscale Convolution Sparse Decomposition
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 In this article, we proposed a novel image fusion method based on multiscale convolution sparse decomposition (MCSD). A unified framework based on MCSD is first utilized to decompose panchromatic (PAN) image and the spatial component of upsampled low ...
Kai Zhang +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Spectral information and backscatter information are both exclusively important bases for land cover classification, and these two kinds of information are found in multispectral images and SAR images, respectively. Therefore, the fusion of complementary
Xunqiang Gong +5 more
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