Results 11 to 20 of about 8,406,664 (294)

Parameter‐adaptive nighttime image enhancement with multi‐scale decomposition

IET Computer Vision, 2016
As a challenging problem, image enhancement plays an important role in computer vision applications and has been widely studied. As one of the most difficult issues of image enhancement, outdoor nighttime image enhancement suffers from noise ...
Shuhang Wang, Jin Zheng, Bo Li
doaj   +2 more sources

A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis [PDF]

Proceedings of the VLDB Endowment
Time series data, including univariate and multivariate ones, are characterized by unique composition and complex multi-scale temporal variations. They often require special consideration of decomposition and multi-scale modeling to analyze.
Li, Guanyao, Song, Sizhe, Zhuo, Weipeng, Zhong, Shuhan, Liu, Yang, Chan, S. -H. Gary   +5 more
core   +6 more sources

Heterogeneous Domain Decomposition for Multi-Scale Problems

43rd AIAA Aerospace Sciences Meeting and Exhibit, 2005
International audienceThe objective of this work is to develop numerical tools useful for the understanding of fundamental phenomena in Blood Flow, including some biochemistry and cellular dynamics.
Christophe Picard, Tran-Son-Tay, Roger, Roger Tran-Son-Tay, Picard, Christophe, Marc Garbey, Garbey, Marc   +5 more
core   +2 more sources

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 ...
Linxiao Yang, Qingsong Wen, Bo Yang 0045, Liang Sun 0001   +3 more
openaire   +3 more sources

Multi scale Harris corner detector based on Differential Morphological Decomposition

Pattern Recognition Letters, 2011
In this paper, a novel method for multi scale corner analysis and detection is presented. First, stateof-the-art Harris–Laplace corner detector is reminded, which benefits from linear scale-space analysis.
L. Gueguen, GUEGUEN Lionel, PESARESI Martino, M. Pesaresi   +3 more
core   +2 more sources

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

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

, 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, Sophia Haussener, Martin Roeb, Thomey, Dennis, Steinfeld, Aldo, Dennis Thomey, Aldo Steinfeld, Haussener, Sophia   +7 more
core   +2 more sources

Medical image enhancement using threshold decomposition driven adaptive morphological filter [PDF]

, 2008
One of the most common degradations in medical images is their poor contrast quality. This suggests the use of contrast enhancement methods as an attempt to modify the intensity distribution of the image.
Mahmoud, Tarek A., Tarek A. Mahmoud, Mahmoud, Tarek, Stephen Marshall, Marshall, Stephen   +4 more
core   +5 more sources

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

Multi-scale proper orthogonal decomposition of complex fluid flows [PDF]

Journal of Fluid Mechanics, 2019
Data-driven decompositions are becoming essential tools in fluid dynamics, allowing for tracking the evolution of coherent patterns in large datasets, and for constructing low-order models of complex phenomena. In this work, we analyse the main limits of two popular decompositions, namely the proper orthogonal decomposition (POD) and the dynamic mode ...
M. A. Mendez, M. Balabane, J.-M. Buchlin
openaire   +2 more sources