Search Results - (( using optimization method algorithm ) OR ( pattern detection utilizing algorithm ))

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    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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    Thesis
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    Iban Plaited Mat Motif Classification using Adaptive Smoothing by Silvia, Joseph

    Published 2024
    “…To address this issue, an improved classification method with adaptive smoothing is proposed. This method utilizes dynamic thresholds for edge detection and uses morphological operations to enhance the smoothed edges. …”
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    Thesis
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    Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni by Farahiyah , Jasni

    Published 2018
    “…The finalized configuration that resulted in the best response was adopted and used to collect data for training and classifying the gait phase using pattern recognition method. …”
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    Thesis
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    Face emotion recognition using artificial intelligence techniques by Kartigayan Muthukaruppan

    Published 2008
    “…The fitness functions are utilized by genetic algorithm (GA) to find the optimized values of minor axes. …”
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    Thesis
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    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column by Othman, M. R., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2003
    “…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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    Conference or Workshop Item
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    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
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    Thesis
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    Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu by Abdul Mannan, Dadu

    Published 2018
    “…The position of reference currents is used to detect the voltage vectors surrounding the reference voltage vector in every sampling period. …”
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    Thesis
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    Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi by Rusdinadi, Saffa Nasuha

    Published 2024
    “…This research aims to improve the detection and analysis of cracks on concrete surfaces by utilizing UAVs and yolo algorithms. …”
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    Student Project
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    Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi by Mohd Pauzi, Mohd Farhan

    Published 2022
    “…This problem occurs due to lacking of existing system in detecting children image in a car. Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. …”
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    Thesis
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    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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    Undergraduates Project Papers
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    Detection of energy theft and defective smart meters in smart grids using linear regression by Yip, S.C., Wong, K., Hew, W.P., Gan, M.T., Phan, R.C.W., Tan, S.W.

    Published 2017
    “…In this paper, we design two linear regression-based algorithms to study consumers’ energy utilization behavior and evaluate their anomaly coefficients so as to combat energy theft caused by meter tampering and detect defective smart meters. …”
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    Article
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    Toward heterogeneous computing to facilitate sequential OLAP real-time applications by Hameed, Shihab A., Habaebi, Mohamed Hadi, Alzeini, Haytham I. M.

    Published 2016
    “…The optimized algorithm is dedicated to detect patterns over parallel data streams in Real-Time. …”
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    Proceeding Paper
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