Search Results - (( motion extraction method algorithm ) OR ( level classification swarm algorithm ))

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  1. 1
    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…Then, the selected features are given as input to the DBN classifier which is trained using the Taylor-based bird swarm algorithm (Taylor-BSA). Taylor-BSA is designed by combining the Taylor series and bird swarm algorithm (BSA).…”
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  2. 2
    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli

    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

    Published 2017
    “…Swarm intelligence (SI) algorithm is implemented because there are lot of previous works which prove that the SI is good for segmentation and classification. …”
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  3. 3
    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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  4. 4
    Fast adaptive motion estimation search algorithm for H.264 encoder

    Fast adaptive motion estimation search algorithm for H.264 encoder by Patwary, Md Anwarul Kaium

    Published 2012
    “…Motion estimation is a technique of video compression and video processing applications; it extracts motion information from the video sequence. …”
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  5. 5
    A new search and extraction technique for motion capture data

    A new search and extraction technique for motion capture data by Mohamad, Rafidei

    Published 2008
    “…Results from the experiments show that matching motion files were successfully extracted from the motion capture library using the new algorithm based on different human body segments.…”
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  6. 6
    An efficient IDS using hybrid Magnetic swarm optimization in WANETs

    An efficient IDS using hybrid Magnetic swarm optimization in WANETs by Sadiq, Ali Safa, Alkazemi, Basem Y., Mirjalili, Seyedali, Noraziah, Ahmad, Khan, Suleman, Ihsan, Ali, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

    Published 2018
    “…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. …”
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  7. 7
    Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition

    Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

    Published 2018
    “…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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  8. 8
    Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter

    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 method employs the RADICAL technique to extract independent subcomponents. …”
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  9. 9
    Component-wise analysis of metaheuristic algorithms for novel fuzzy-meta classifier

    Component-wise analysis of metaheuristic algorithms for novel fuzzy-meta classifier by Talfur, Khasif Hussain

    Published 2018
    “…This research selected three commonly used swarm-based metaheuristic algorithms – Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Cuckoo Search (CS) – to perform component-wise analysis. …”
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  10. 10
    An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs

    An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs by Sadiq, Ali Safaa, Alkazemi, Basem, Mirjalili, Seyedali, Ahmed, Noraziah, Khan, Suleman, Ali, Ihsan, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

    Published 2018
    “…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. …”
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  11. 11
    Predicting the classification of heart failure patients using optimized machine learning algorithms

    Predicting the classification of heart failure patients using optimized machine learning algorithms by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md Maruf, Bhuiyan, Touhid

    Published 2025
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  12. 12
    Software defect prediction framework based on hybrid metaheuristic optimization methods

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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  13. 13
    Motion detection using Horn-Schunck optical flow

    Motion detection using Horn-Schunck optical flow by Wan Nur Azhani, W. Samsudin, Kamarul Hawari, Ghazali

    Published 2012
    “…This system is design to detect motion in a crowd using one of the optical flow algorithms, Horn-Schunck method. …”
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  14. 14
    Particle swarm optimization with deep learning for human action recognition

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…This decreases the detection efficiency and degrades the target tracking output. Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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  15. 15
    A method for motion tracking of ventricular endocardial surface

    A method for motion tracking of ventricular endocardial surface by O. K. Rahmat, Rahmita Wirza, Dawood, Faten Abed Ali, Dimon, Mohd Zamrin, Kadiman, Suhaini, Abdullah, Lili Nurliyana

    Published 2014
    “…The present invention relates to a method for automatic motion tracking of ventricular endocardial surface in three dimensional (3D) echocardiography, characterized by the steps of extracting a plurality of ventricular endocardial contours over a complete cardiac cycle; identifying a plurality of landmarks on each ventricular endocardial contour; measuring displacement vector flow (DVF) for each landmark by comparing a pair of consecutive ventricular endocardial contours; measuring velocity vector flow (VVF) for each landmark from end-diastolic (ED) to end-systolic (ES) and vice versa; identifying at least four landmarks from the plurality of landmarks on each ventricular endocardial contour to represent anatomical landmarks of left lateral surface, right lateral surface, inferior wall and anterior wall by using geometrical distance calculation (GDC) algorithm; analysing ventricular endocardial motion direction using a fuzzy logic analyzer (FLA) for the four landmarks identified; updating values of the displacement vector flow (DVF) and velocity vector flow (VVF) based on the ventricular endocardial motion direction; and generating graphical curves of time versus values of the displacement vector flow (DVF) and velocity vector flow (VVF) for the four landmarks identified.…”
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  16. 16
    Design and performance analysis of artificial neural network for hand motion detection from EMG signals

    Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

    Published 2013
    “…The conventional and most effective time and timefrequency based features are extracted and normalized. The neural network has been trained with the normalized feature set with supervised learning method. …”
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  17. 17
    Detection and Classification of Moving Objects for an Automated Surveillance System

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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  18. 18
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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  19. 19
    Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing

    Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing by Alsaaidah, Yousef A., Muhammed, Abdullah, Ala’anzy, Mohammed Alaa, Othman, Mohamed, Abdullah, Azizol

    Published 2025
    “…It enhances the locust-inspired algorithm by integrating SLA-awareness and adaptive host classification and is evaluated using real workload traces in the CloudSim toolkit. …”
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  20. 20
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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