Automated diagnosis of COVID stages using texture‐based Gabor features in variational mode decomposition from CT images
Sign Up to like & getrecommendations! Published in 2023 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22865
Abstract: COVID‐19 is a deadly and fast‐spreading disease that makes early death by affecting human organs, primarily the lungs. The detection of COVID in the early stages is crucial as it may help restrict the spread… read more here.
Keywords: mode decomposition; covid; diagnosis covid; texture based ... See more keywords
Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition
Sign Up to like & getrecommendations! Published in 2017 at "Machine Vision and Applications"
DOI: 10.1007/s00138-017-0835-5
Abstract: Images of the kidneys using dynamic contrast-enhanced magnetic resonance renography (DCE-MRR) contains unwanted complex organ motion due to respiration. This gives rise to motion artefacts that hinder the clinical assessment of kidney function. However, due… read more here.
Keywords: dynamic mode; windowed reconstruction; movement correction; movement ... See more keywords
Bivariate 2D empirical mode decomposition for analyzing instantaneous turbulent velocity field in unsteady flows
Sign Up to like & getrecommendations! Published in 2019 at "Experiments in Fluids"
DOI: 10.1007/s00348-019-2775-5
Abstract: We introduce and demonstrate the bivariate two-dimensional empirical mode decomposition (bivariate 2D-EMD) for the decomposition of a turbulent instantaneous velocity field to separate spatial large-scale organized motion from random turbulent fluctuations. To validate this approach,… read more here.
Keywords: velocity field; velocity; decomposition; empirical mode ... See more keywords
Real-time states estimation of a farm tractor using dynamic mode decomposition
Sign Up to like & getrecommendations! Published in 2020 at "GPS Solutions"
DOI: 10.1007/s10291-020-01051-5
Abstract: We present a pure data-driven method to estimate vehicle dynamics from the measurements of sideslip and yaw rate in the use of GPS and inertial navigation system. The GPS and INS configuration provides vehicle position,… read more here.
Keywords: dynamic mode; mode decomposition; real time; vehicle ... See more keywords
The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm
Sign Up to like & getrecommendations! Published in 2020 at "Annals of Operations Research"
DOI: 10.1007/s10479-020-03690-w
Abstract: As stock data is characterized by highly noisy and non-stationary, stock price prediction is regarded as a knotty problem. In this paper, we propose new two-stage ensemble models by combining empirical mode decomposition (EMD) (or… read more here.
Keywords: machine; mode decomposition; elm; price prediction ... See more keywords
Hierarchical decomposition based on a variation of empirical mode decomposition
Sign Up to like & getrecommendations! Published in 2017 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-016-1024-0
Abstract: Adaptive methods of signal analysis have proved a very useful tool for analysis of non-stationary signals. This is due to the ability of these methods to adapt to the local structures of the signals being… read more here.
Keywords: mode decomposition; frequency; emd; empirical mode ... See more keywords
Band selection using variational mode decomposition applied in sparsity-based hyperspectral unmixing algorithms
Sign Up to like & getrecommendations! Published in 2018 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-018-1301-1
Abstract: In this work, a frequency-based dimensionality reduction technique using variational mode decomposition (VMD) is proposed. Dimensionality reduction is a very important aspect of preprocessing in case of hyperspectral image (HSI) analysis where this step helps… read more here.
Keywords: variational mode; using variational; band; dimensionality reduction ... See more keywords
A data-driven strategy for xenon dynamical forecasting using dynamic mode decomposition
Sign Up to like & getrecommendations! Published in 2020 at "Annals of Nuclear Energy"
DOI: 10.1016/j.anucene.2020.107826
Abstract: Abstract Detection and prediction of xenon induced oscillations are an important part in the operation of pressurized water reactors. Several models have been proposed for the prediction or estimation of xenon oscillations with drawbacks e.g.… read more here.
Keywords: dynamic mode; mode decomposition; xenon; data driven ... See more keywords
Grain size characterization of aluminum based on ensemble empirical mode decomposition using a laser ultrasonic technique
Sign Up to like & getrecommendations! Published in 2019 at "Applied Acoustics"
DOI: 10.1016/j.apacoust.2019.07.030
Abstract: Abstract In this study, an effective approach was presented for the decomposition and reconstitution of ultrasonic signals and the creation of a prediction model to characterize the average grain size of materials via a nondestructive… read more here.
Keywords: decomposition; grain size; empirical mode; mode decomposition ... See more keywords
A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with Bayesian optimization algorithm
Sign Up to like & getrecommendations! Published in 2019 at "Applied Energy"
DOI: 10.1016/j.apenergy.2019.01.055
Abstract: Short-term load forecasting plays an essential role in the safe and stable operation of power systems and has always been a vital research issue of energy management. In this research, a hybrid short-load forecasting method… read more here.
Keywords: term; long short; memory; short term ... See more keywords
Scale dependent prediction of reference evapotranspiration based on Multi-Variate Empirical mode decomposition
Sign Up to like & getrecommendations! Published in 2018 at "Ain Shams Engineering Journal"
DOI: 10.1016/j.asej.2016.10.014
Abstract: This study proposes a novel method for estimation of reference evapotranspiration (ETo) by accounting the time scale of variability using the Multivariate Empirical Mode Decomposition (MEMD). First the ETo and the four predictor variables such… read more here.
Keywords: empirical mode; reference evapotranspiration; mode; mode decomposition ... See more keywords