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  1. 1
    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming

    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Sebastian, P., Hamid, N.H.B., Ahmed, E.F.

    Published 2022
    “…Thus, related surveillance planning methods optimize the placement of visual sensors based on equally significance grids by not limiting to demand of coverage. …”
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  2. 2
    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
    “…An optimization and eigen-decomposition-based subspace approach has been investigated and tested to estimate the latencies of visual evoked potential (VEP) signals which are highly corrupted by spontaneous electro-encephalogram (EEG) waveforms that can be considered as colored noise. …”
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  3. 3
    A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise

    A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise by Yusoff, Mohd Zuki, Hussin, Fawnizu Azmadi

    Published 2010
    “…An optimization and eigen-decomposition-based subspace approach has been investigated and tested to estimate signals which are highly corrupted by colored noise; Hu and Loizou [Y. …”
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  4. 4
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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    Thesis
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  5. 5
    Detecting and evaluating surface crack defect of building structure and infrastructure elements using Digital Image Processing approach / Nursyafiqah Razmi

    Detecting and evaluating surface crack defect of building structure and infrastructure elements using Digital Image Processing approach / Nursyafiqah Razmi by Razmi, Nursyafiqah

    Published 2018
    “…By using this technique, the surface cracked area on damaged structures was detected appropriately and the crack length was estimated with small error of 0.5 to 4.62 percent from the actual crack length observed by the visual inspection method. …”
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  6. 6
    Deep Reinforcement Learning For Control

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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    Monograph
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  7. 7
    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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    Thesis
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  14. 14
    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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  15. 15
    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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  16. 16
    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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  17. 17
    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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  18. 18
    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…Therefore, the SMA method is redesigned for optimal location and sizing based on the total active power loss of the systems. …”
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  19. 19
    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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  20. 20
    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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