Results 21 to 30 of about 781,103 (334)

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

open access: yesJournal 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   +5 more
semanticscholar   +1 more source

Multi-Scale Modelling of a Solar Reactor for the High-Temperature Step of a Sulphur-Iodine-Based Water Splitting Cycle [PDF]

open access: yes, 2011
The 3-step sulphur-iodine-based thermochemical cycle for splitting water is considered. The high temperature step of the closed-material cycle consists of evaporation, decomposition, and reduction of sulphuric acid to SO2 using concentrated solar process
Roeb, Martin   +7 more
core   +1 more source

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

open access: yesJournal 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   +4 more
doaj   +1 more source

Subspace Decomposition based DNN algorithm for elliptic type multi-scale PDEs [PDF]

open access: yesJournal of Computational Physics, 2021
While deep learning algorithms demonstrate a great potential in scientific computing, its application to multi-scale problems remains to be a big challenge.
Xi-An Li, Z. Xu, Lei Zhang
semanticscholar   +1 more source

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

open access: yes2021 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

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

open access: yesEntropy, 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   +5 more
doaj   +1 more source

Fast multi-scale detail decomposition via accelerated iterative shrinkage [PDF]

open access: yesSIGGRAPH Asia 2013 Technical Briefs, 2013
We present a fast solution for performing multi-scale detail decomposition. The proposed method is based on an accelerated iterative shrinkage algorithm, able to process high definition color images in real-time on modern GPUs. Our strategy to accelerate the smoothing process is based on the use of first order proximal operators.
Badri, Hicham   +2 more
openaire   +2 more sources

Agile multi-scale decompositions for automatic image registration [PDF]

open access: yesSPIE Proceedings, 2016
In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone.
James M. Murphy   +2 more
openaire   +1 more source

Deep Residual Transform for Multi-scale Image Decomposition

open access: yesJournal 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   +4 more
openaire   +2 more sources

Spatio‐temporal multi‐scale motion descriptor from a spatially‐constrained decomposition for online action recognition

open access: yesIET Computer Vision, 2017
This study presents a spatio‐temporal motion descriptor that is computed from a spatially‐constrained decomposition and applied to online classification and recognition of human activities.
Fabio Martínez   +2 more
doaj   +1 more source

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