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  1. 1

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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    Thesis
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    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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  3. 3

    Model-based hybrid variational level set method applied to lung cancer detection by Jing, Wang, Liew, Siau-Chuin, Azian, Abd Aziz

    Published 2024
    “…This algorithm simplifies the (Local Intensity Clustering) LIC model and devises a new energy functional based on the region-based pressure function. …”
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  4. 4

    Variational model with image denoising fitting term for boundary extraction of breast ultrasound images by Badrulhisam, Nurdina, Ismail, Nurhuda, Jumaat, Abdul Kadir, Maasar, Mohd Azdi, Laham, Mohamed Faris

    Published 2023
    “…Consideration of four distinct image Denoising algorithms—Gaussian filter, Median filter, Wiener filter, and Rudin-OsherFatemi (ROF) algorithm—as the new fitting terms in the CDSS model leads to four variants of modified CDSS models called Modified CDSS based on Gaussian filter (MCDSSG), Modified CDSS based on Median filter (MCDSSM), Modified CDSS based on Wiener filter (MCDSSW) and Modified CDSS based on ROF (MCDSSROF). …”
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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
    “…Then, GA and HS algorithms are used as recognition-based segmentation phase for text and character recognition respectively. …”
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    Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

    Published 2021
    “…Thus, this research aimed to estimate large-scale kinetic parameters of the main metabolic pathway of the E. coli model. In this regard, a Local Sensitivity Analysis, Segment Particle Swarm Optimization (Se-PSO) algorithm, and the Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm was adapted and proposed to estimate the parameters. …”
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  9. 9

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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  10. 10

    A rule-based image segmentation method and neural network model for classifying fruit in natural environment / Hamirul'aini Hambali by Hambali, Hamirul'aini

    Published 2015
    “…However, Adaptive K-means has limitation in segmenting black images. Therefore, the improved thresholding-based segmentation (TsN) is integrated with the Adaptive K-means thus resulting in rule-based segmentation namely TsNKM method. …”
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    Thesis
  11. 11

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  14. 14

    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  15. 15

    Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

    Published 2024
    “…VKMHLS simplifies the Local Intensity Clustering (LIC) model and introduces a novel energy functional based on the region-based pressure function, enhancing the efficiency of segmentation for low grayscale images. …”
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    Thesis
  16. 16

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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  17. 17

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

    Published 2018
    “…The fade transitions are detected based on the smoothed moments energy and the moments of gradients correlation for the candidate segments. …”
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    Thesis
  18. 18

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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  19. 19

    Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

    Published 2024
    “…Following the successful detection and segmentation of the plants, another YOLOv8 based model was further developed to segment individual leaves from detected plant. …”
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    Final Year Project / Dissertation / Thesis
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