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  1. 1

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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    Thesis
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    Fraud detection in telecommunication industry using Gaussian mixed model by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

    Published 2013
    “…The expectation maximization algorithm is used to estimate the parameter of the model such that the initial values of the algorithm is determined using the kernel method. …”
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    Conference or Workshop Item
  4. 4

    Novel algorithms of identifying types of partial discharges using electrical and non-contact methods / Mohammad Shukri Hapeez by Hapeez, Mohammad Shukri

    Published 2015
    “…FPDI uses simple probe and oscilloscope for detection while the competitors are using the PD circuit detector. …”
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    Thesis
  5. 5

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
    Article
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    An evolutionary harmony search algorithm with dominant point detection for recognition-based segmentation of online Arabic text recognition by Moayad, Yousif Potrus, Ngah, Umi Kalthum, Bestoun S. , Ahmed

    Published 2014
    “…At first, the pre-segmentation algorithm uses a modified dominant point detection algorithm to mark a minimal number of points which defines the text skeleton. …”
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    Article
  7. 7

    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff by Md Ariff, Norharyati

    Published 2007
    “…Genetic algorithms have several steps. For the initial population, 200 pixels will be taken to be the initial population in randomly. …”
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    Thesis
  8. 8

    Semi-automatic cortical boundary detection / Noor Elaiza Abdul Khalid. by Abdul Khalid, Noor Elaiza

    Published 2010
    “…FPSO incorporates fuzzy edge detection technique as the initial population and the optimum membership value as the fitness function in the particle swarm optimization algorithm. …”
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    Thesis
  9. 9

    Detection on ambiguous software requirements specification written in malay using machine learning by Zahrin, Mohd Firdaus

    Published 2017
    “…Hence, we propose a framework to detect ambiguity on SRS using supervised machine learning technique. …”
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    Thesis
  10. 10

    Facial Drowsiness Signs Detection Algorithm Using Image Processing Techniques For Various Lighting Condition by Yuri, Nur Fatin Izzati

    Published 2017
    “…In this project, the algorithm is developed based on four main algorithms which are the detection algorithm, the tracking algorithm, the preprocessing algorithm and the drowsiness signs analysis algorithm. …”
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    Thesis
  11. 11

    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

    Published 2018
    “…In addition, the wipe and dissolve transitions are detected using the change-point detection technique, SVM model, and scale invariant feature transform (SIFT). …”
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    Thesis
  12. 12

    A Fast Vertical Edge Detection Algorithm for Car License Plate Detection by Ali Al-Ghaili, Abbas Mohammed

    Published 2009
    “…This thesis aims to propose a fast vertical edge detector using Vertical Edge Detection Algorithm (VEDA) and to build a Car License Plate Detection (CLPD) method. …”
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    Thesis
  13. 13

    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

    Published 2018
    “…Thus, the optimization of the randomly detectors of V-Detectors algorithm with CSDE is proficient and suitable for anomaly detection tasks.…”
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    Thesis
  14. 14

    A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

    Published 2019
    “…Machine learning approaches have been widely used to increase the effectiveness of intrusion detection platforms. …”
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    Thesis
  15. 15

    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

    Published 2024
    “…The "Remote to Local (R2L) Intrusion Detection System Using Decision Tree" project aims to address the escalating threat of network intrusions by developing an effective intrusion detection system. …”
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    Thesis
  16. 16

    Development of vehicle detection and counting system for traffic analysis using computer vision by Saw, Kenny Wei Wen

    Published 2024
    “…Once the trained weights are ready a deep learning algorithm detection model is applied to detect and draw a bounding box on the vehicles. …”
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    Final Year Project / Dissertation / Thesis
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    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…Expectation–Maximization algorithm is a novel method used by us for the first time for identifying renal stones. …”
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    Proceedings
  18. 18

    Cars detection in stitched image using morphological approach by Joselyn, Jok.

    Published 2017
    “…The performance of the proposed cars detection algorithm could detect the cars fairly accurate. …”
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    Final Year Project Report / IMRAD
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    Improved expectation maximization algorithm for Gaussian mixed model using the kernel method by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

    Published 2013
    “…We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. …”
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    Article