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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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    Proceeding Paper
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  4. 4
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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  5. 5
    Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization

    Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization by Kamal Zuhairi, Zamli, Din, Fakhrud, Alhadawi, Hussam S.

    Published 2023
    “…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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  6. 6
    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection

    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…The proposed method is validated with ten benchmark datasets from UCI machine learning repository. To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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  7. 7
    Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system

    Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abd Ghani

    Published 2022
    “…The SDA is a simple-structured and deterministic type of algorithm, which also performs competitively in terms of solution accuracy. …”
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  8. 8
    Machine learning based route optimization for the travelling salesman problem with pickup and delivery

    Machine learning based route optimization for the travelling salesman problem with pickup and delivery by Ong, Zhi Ying

    Published 2023
    “…Consequently, the courier cost will increase, which leads to in low customer satisfaction due to long pickup and delivery time, particularly during peak hours. The goal of this project is to deliver an optimal route for pickup and delivery using Reinforcement Learning (RL) and Genetic Algorithm (GA). 16 locations in Klang Valley are chosen randomly and later ETAs between them are retrieved for testing purpose. …”
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  9. 9
    Integration of GWO-LSSVM for time series predictive analysis

    Integration of GWO-LSSVM for time series predictive analysis by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Bariah, Yusob, Ernawan, Ferda

    Published 2016
    “…The emergence of Statistical Learning Theory (SLT) based algorithm namely Least Squares Support Vector Machines (LSSVM) has evidenced its efficacy in solving regression and classification problems. …”
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  10. 10
    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm

    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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  11. 11
    Automated Vehicle Classification (AVC) using machine learning implementation in Malaysia's toll system

    Automated Vehicle Classification (AVC) using machine learning implementation in Malaysia's toll system by Hassan, Raini, Mohd Ridzal, Aisyah Afiqah, Fadzleey, Nur Zulfah Insyirah

    Published 2024
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  12. 12
    Machine learning application in predicting anterior cruciate ligament injury among basketball players

    Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

    Published 2025
    “…A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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  13. 13
    Dynamic role engine and formation control for cooperating agents

    Dynamic role engine and formation control for cooperating agents by S. Hamidreza, Kasaei, S. Mohammadreza, Kasaei, S. Alireza, Kasaei, Mohsen, Taheri

    Published 2009
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  14. 14
    A Neural Network Mobile Learning Application For Autonomous Improvement In A Flexible Manufacturing Environment

    A Neural Network Mobile Learning Application For Autonomous Improvement In A Flexible Manufacturing Environment by Siew , Jit Ping

    Published 2016
    “…Modern manufacturing has evolved into a very competitive industry and wastages resulting from process defects are very costly. …”
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  15. 15
    A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar

    A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

    Published 2007
    “…In this project, the networks were trained using certain types training algorithm depending on the types of networks; Levenberg Marquardt (LM) for the MLP, competitive network for the LVQ and hybrid learning for ANFIS. …”
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    Research Reports
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  16. 16
    The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach

    The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach by Muhammad Ar Rahim, Ibrahim, Muhammad Amirul, Abdullah, Muhammad Nur Aiman, Shapiee, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Muhammad Aizzat, Zakaria, Noor Azuan, Abu Osman, Anwar P. P., Abdul Majeed

    “…The evaluation of skateboarding tricks is commonly carried out subjectively through the prior experience of the panel of judges during skateboarding competitions. Hence, this technique evaluation is often impartial to a certain degree. …”
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