Search Results - (( based estimation method algorithm ) OR ( rate extraction method algorithm ))

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  1. 1

    Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter by Nooralishahi, Parham, Loo, Chu Kiong, Shiung, Liew Wei

    Published 2019
    “…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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    Article
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    Multi-trial extended subspace-based approach for visually evoked potentials (VEPs) extraction by Kamel , Nidal, Malik, Aamir Saeed

    Published 2013
    “…The results indicate close performance by the proposed technique to EA in terms of bias and failure rate. Conclusion: A multi-trial subspace-based algorithm is proposed to extract the VEPs from the brain background colored noise. …”
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    Citation Index Journal
  5. 5

    Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

    Published 2016
    “…A single-trial extraction of a visual evoked potential (VEP) signal based on the partial least-squares (PLS) regression method has been proposed in this paper. …”
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    Article
  6. 6

    Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

    Published 2016
    “…A single-trial extraction of a visual evoked potential (VEP) signal based on the partial least-squares (PLS) regression method has been proposed in this paper. …”
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    Article
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    Signal quality measures for pulse oximetry through waveform morphology analysis by Sukor, J. Abdul, Redmond, S. J., Lovell, N. H.

    Published 2011
    “…A mean κ of 0.64 ± 0.22 was obtained, while the mean sensitivity, specificity and accuracy were 89 ± 10%, 77 ± 19% and 83 ± 11%, respectively. Furthermore, a heart rate estimate, extracted from uncontaminated sections of PPG, as identified by the algorithm, was compared with the heart rate derived from an uncontaminated simultaneous ECG signal. …”
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    Article
  9. 9

    Region duplication forgery detection technique based on keypoint matching / Diaa Mohammed Hassan Uliyan by Diaa , Mohammed Hassan Uliyan

    Published 2016
    “…The average detection rate of our algorithm maintained 96 % true positive rate and 7 % false positive rate which outperform several current detection methods. …”
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    Thesis
  10. 10

    Subspace Techniques for Brain Signal Enhancement by Kamel , Nidal, Yusoff, Mohd Zuki

    Published 2009
    “…Both the simulation and real human data show that the subspace methods generate reasonably low errors and high success rate. …”
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    Book Section
  11. 11

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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    Thesis
  12. 12

    Facial age range estimation using geometric ratios and hessian-based filter wrinkle analysis by Razalli, Husniza

    Published 2016
    “…The Hessian-Based Filter is used to enhance wrinkle analysis for age range estimation method. …”
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    Thesis
  13. 13

    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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    Thesis
  14. 14

    Age detection from face using Convolutional Neural Network (CNN) / Hanin Hanisah Usok @ Yusoff by Usok @ Yusoff, Hanin Hanisah

    Published 2024
    “…Following a thorough examination of numerous algorithms, CNN was determined to be the best effective method for age recognition from facial features due to its ability to automatically extract important data. …”
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    Thesis
  15. 15

    Estimation of non-contact smartphone video-based vital sign monitoring using filtering and standard color conversion techniques by Qayyum, A., Malik, A.S., Shuaibu, A.N., Nasir, N.

    Published 2018
    “…This rPPG signal could perform better as compared to the standard vital signs estimation methods. The Inter beat interval (IBI) based on maximum peak detection approach has been used for heart rate variability estimation. …”
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    Article
  16. 16

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…Moreover, the LSA optimization technique is introduced to optimally determine the LSTM deep neural model hyperparameters including the number of hidden neurons, learn rate, epoch, learn rate drop factor, learn rate drop period, and gradient decay factor. …”
    Article
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    Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

    Published 2019
    “…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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    Article
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    Ensemble averaging subspace-based approach for ERP extraction by Kamel, Nidal, Malik, Aamir, Jatoi, Munsif Ali

    Published 2013
    “…A novel approach based on Subspace methods is proposed for extracting the Event Related Potentials (ERPs) from the background Electroencephalograph (EEG) colored noise. …”
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    Conference or Workshop Item
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    Comparisons of Signal Subspace Methods for Estimating Visual Evoked Potentials by Yusoff, Mohd Zuki, Nidal S., Kamel

    Published 2008
    “…These algorithms denoted as Signal Subspace Method 1 (SSM1) and Signal Subspace Method 2 (SSM2) are able to satisfactorily extract the P100, P200 and P300 peak latencies from artificially generated noisy VEPs subjected to SNRs from 0 to -10 dB. …”
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    Conference or Workshop Item