Results 31 to 40 of about 1,165,616 (316)

The Study of Feature Extraction Method Based on Multi-scale Morphological Spectrum Entropy

Chemical Engineering Transactions, 2016
Multi-scale morphological decomposition is a decomposition method being proposed based on the basic theory of multi-scale morphology. Using from small to large scale of structural elements to deal with different “Scale domain”, thus the original signal ...
H.M. Ge, L. Chen, J. Liang
doaj   +1 more source

One Dimensional Convolutional Neural Networks Using Sparse Wavelet Decomposition for Bearing Fault Diagnosis

IEEE Access, 2022
This paper proposes a novel algorithm for bearing fault diagnosis using sparse wavelet decomposition for feature extraction combined with a multi-scale one dimensional convolutional neural network (1-D CNN).
Xiaofan Liu, Jason Centeno, Juan Alvarado, Lizhe Tan   +3 more
doaj   +1 more source

Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition [PDF]

, 2017
This paper focuses on multi-scale approaches for variational methods and corresponding gradient flows. Recently, for convex regularization functionals such as total variation, new theory and algorithms for nonlinear eigenvalue problems via nonlinear ...
A Chambolle, A Haddad, A Hoover, C Brune, C Wu, C Zach, D Strong, G Bellettini, G Gilboa, G Gilboa, G Gilboa, J Yuan, JF Aujol, L Zeune, M Burger, M Burger, M Nikolova, S Osher, TF Chan, V Caselles, V Duval, W Yin, Y Dong   +22 more
core   +3 more sources

Deep Residual Transform for Multi-scale Image Decomposition

Journal of Computational Vision and Imaging Systems, 2021
Multi-scale image decomposition (MID) is a fundamental task in computer vision and image processing that involves the transformation of an image into a hierarchical representation comprising of different levels of visual granularity from coarse structures to fine details.
Linlin Xu, Yifan Wu, Yuan Fang, Alexander Wong, Yuhao Chen   +4 more
openaire   +2 more sources

Multi-scale reconstruction of turbulent rotating flows with proper orthogonal decomposition and generative adversarial networks [PDF]

Journal of Fluid Mechanics, 2022
Data reconstruction of rotating turbulent snapshots is investigated utilizing data-driven tools. This problem is crucial for numerous geophysical applications and fundamental aspects, given the concurrent effects of direct and inverse energy cascades ...
Tianyi Li, M. Buzzicotti, Luca Biferale, F. Bonaccorso, Shiyi Chen, M. Wan   +5 more
semanticscholar   +1 more source

A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition [PDF]

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Many real-world time series exhibit multiple seasonality with different lengths. The removal of seasonal components is crucial in numerous applications of time series, including forecasting and anomaly detection. However, many seasonal-trend decomposition algorithms suffer from high computational cost and require a large amount of data when multiple ...
Yang, Linxiao, Wen, Qingsong, Yang, Bo, Sun, Liang   +3 more
openaire   +2 more sources

GA-PE-VMD and MSE Methods for Milling Chatter Feature Extraction of Thin-walled Parts

Journal of Harbin University of Science and Technology, 2023
In the high-speed milling of aviation parts, due to the low stiffness of thin-walled structure, it is easy to produce chatter. Chatter leads to poor surface quality, dimensional error and reducing the service life of tools and machines.Therefore, a ...
WANG Hanbin, LI Maoyue, LIU Xianli, WANG Zhixue, MENG Boyang   +4 more
doaj   +1 more source

Multi-scale Image Decomposition Using a Local Statistical Edge Model [PDF]

2021 IEEE 7th International Conference on Virtual Reality (ICVR), 2021
We present a progressive image decomposition method based on a novel non-linear filter named Sub-window Variance filter. Our method is specifically designed for image detail enhancement purpose; this application requires extraction of image details which are small in terms of both spatial and variation scales.
openaire   +2 more sources

Multi-focus image fusion using multi-scale image decomposition and saliency detection

Ain Shams Engineering Journal, 2018
In this paper, we develop a new multi-focus image fusion method based on saliency detection and multi-scale image decomposition. Proposed method is very efficient, since the visual saliency explored in this algorithm is able to emphasize visually ...
Durga Prasad Bavirisetti, Ravindra Dhuli
doaj   +1 more source

Entropy-Based Image Fusion with Joint Sparse Representation and Rolling Guidance Filter

Entropy, 2020
Image fusion is a very practical technology that can be applied in many fields, such as medicine, remote sensing and surveillance. An image fusion method using multi-scale decomposition and joint sparse representation is introduced in this paper.
Yudan Liu, Xiaomin Yang, Rongzhu Zhang, Marcelo Keese Albertini, Turgay Celik, Gwanggil Jeon   +5 more
doaj   +1 more source