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  1. 1
    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments

    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

    Published 2022
    “…Visual odometry is the process of estimating the motion between two consecutive images. …”
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  2. 2
    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments

    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

    Published 2022
    “…Visual odometry is the process of estimating the motion between two consecutive images. …”
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  3. 3
    Parallel visualization approach of a 3D heart model

    Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

    Published 2008
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  4. 4
    Natural image noise level estimation based on local statistics for blind noise reduction

    Natural image noise level estimation based on local statistics for blind noise reduction by Khmag, Asem, Ramli, Abd Rahman, Sy Mohamed, Sy Abd Rahman Al-haddad, Kamarudin, Noraziahtulhidayu

    Published 2018
    “…In this study, a patch-based estimation technique is used to estimate for noise level and applies it to the proposed blind image denoising algorithm. …”
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  5. 5
    A Time-Domain Subspace Technique for Estimating Visual Evoked Potential Latencies

    A Time-Domain Subspace Technique for Estimating Visual Evoked Potential Latencies by Yusoff, Mohd Zuki, Kamel, Nidal

    Published 2010
    “…Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-noise ratio (SNR) is generally very low. …”
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  6. 6
    Estimation of Visual Evoked Potentials using a Signal Subspace Approach

    Estimation of Visual Evoked Potentials using a Signal Subspace Approach by Kamel , Nidal

    Published 2007
    “…The signal subspace is estimated by applying eigenvalue decomposition on the approximated signal covariance matrix. …”
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  7. 7
    EEG-based brain source localization using visual stimuli

    EEG-based brain source localization using visual stimuli by Jatoi, M.A., Kamel, N., Malik, A.S., Faye, I., Bornot, J.M., Begum, T.

    Published 2016
    “…According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. …”
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  8. 8
    Single-trial visual evoked potential extraction using partial least-squares-based approach

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

    Published 2016
    “…The PLS algorithm gives the best estimate to multitrial ensemble averaging. …”
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  9. 9
    Single-trial visual evoked potential extraction using partial least-squares-based approach

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

    Published 2016
    “…The PLS algorithm gives the best estimate to multitrial ensemble averaging. …”
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  10. 10
    JMASM algorithms and code algorithm for combining robust and bootstrap in multiple linear model regression (SAS)

    JMASM algorithms and code algorithm for combining robust and bootstrap in multiple linear model regression (SAS) by Wan Muhamad Amir, Mohamad Shafiq, Hanafi A. Rahim, Puspa Liza Ghazali, Azlida Aleng, Abdullah, Z.

    Published 2016
    “…The aim of bootstrapping is to approximate the sampling distribution of some estimator. An algorithm for combining method is given in SAS, along with applications and visualizations.…”
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  11. 11
    Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images

    Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images by Khan, A., Ali, S.S.A., Anwer, A., Adil, S.H., Meriaudeau, F.

    Published 2018
    “…This paper presents a new method for subsea pipeline corrosion estimation by using colour information of corroded pipe. …”
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  12. 12
    Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images

    Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images by Khan, A., Ali, S.S.A., Anwer, A., Adil, S.H., Meriaudeau, F.

    Published 2018
    “…This paper presents a new method for subsea pipeline corrosion estimation by using colour information of corroded pipe. …”
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  13. 13
    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment

    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment by Aqel, Mohammad O. A.

    Published 2016
    “…The most important task for any autonomous mobile vehicle is the reliable estimation of its position over time. Visual odometry (VO) is a localization technique that estimates the position of a robot using only the stream of images acquired from a camera. …”
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  14. 14
    GMSD-based perceptually motivated non-local means filter for image denoising

    GMSD-based perceptually motivated non-local means filter for image denoising by Baqar, Mohtashim *, Lau, Sian Lun *

    Published 2019
    “…Further, the proposed methodology also helps in mitigating the patch jittering blur effect (PJBE) and over smoothing of denoised images as observed with conventional NLM algorithm. Experimental evaluations based on visual-quality assessment and least-square based metrics have shown that the proposed algorithm yields better denoised image estimates than the conventional NLM algorithm. …”
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  15. 15
    Estimation of Visual Evoked Potentials using a Signal Subspace Approach

    Estimation of Visual Evoked Potentials using a Signal Subspace Approach by Yusoff, Mohd Zuki, Kamel , Nidal, Ahmad Fadzil, Mohd Hani

    Published 2007
    “…A signal subspace technique is presented to estimate VEPs hidden inside highly colored electroencephalogram EEG) noise. …”
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  16. 16
    Estimation of Visual Evoked Potentials using a Signal Subspace Approach

    Estimation of Visual Evoked Potentials using a Signal Subspace Approach by Kamel , Nidal

    Published 2007
    “…The signal subspacebased algorithm is able to satisfactorily extract the P100, P200and P300 peak latencies from artificially generated noisy VEPs.The simulation results show that the estimator maintains anaverage success rate of 87 % with an average percentage error of less than 9 %, when subjected to SNR from 0 dB to -10 dB. …”
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  17. 17
    Generalized Subspace Approach for Measurements of Visual Evoked Potentials

    Generalized Subspace Approach for Measurements of Visual Evoked Potentials by Yusoff, Mohd Zuki

    Published 2009
    “…Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-noise ratio (SNR) is generally very low. …”
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  18. 18
    Generalized Subspace Approach for Measurement of Latencies in Visual Evoked Potentials

    Generalized Subspace Approach for Measurement of Latencies in Visual Evoked Potentials by Yusoff, Mohd Zuki

    Published 2010
    “…Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-noise ratio (SNR) is generally very low. …”
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  19. 19
    Tracking of dynamic arm motion estimation and interaction with fuzzy control

    Tracking of dynamic arm motion estimation and interaction with fuzzy control by Badi, Haitham, Hamza, Alaa, Mohd Yunus, Mohd Amin

    Published 2016
    “…For robustly tracking the users arm position, an arm motion estimation method is designed based on the fuzzy predictive control fuzzy Mamdani algorithm theory. …”
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  20. 20
    Improved abnormal detection using self-adaptive social force model for visual surveillance

    Improved abnormal detection using self-adaptive social force model for visual surveillance by Wan Nur Azhani, W. Samsudin

    Published 2017
    “…For both indoor and outdoor scene, the proposed algorithm outperforms the other methods with accuracy 97% and 100%. …”
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