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  1. 1
    Designing and Developing an Intelligent Congkak

    Designing and Developing an Intelligent Congkak by Muhammad Safwan, Mohd Shahidan

    Published 2011
    “…and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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  2. 2
    Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud

    Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud by Mahmud, Nur Farahana

    Published 2022
    “…However, according to a recent study, ANN algorithms require a huge amount of training data while BPFFNN algorithms only have an average success rate of 70% in recognizing all the characters. …”
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  3. 3
    Brain Machine Interface Controlled Robot Chair

    Brain Machine Interface Controlled Robot Chair by Hema Chengalvarayan, Radhakrishnamurthy

    Published 2010
    “…A particle swarm optimization based algorithm is proposed to train the neural networks. …”
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  4. 4
    Development of colorization of grayscale images using CNN-SVM

    Development of colorization of grayscale images using CNN-SVM by Abualola, Abdallah, Gunawan, Teddy Surya, Kartiwi, Mira, Ambikairajah, Eliathamby, Habaebi, Mohamed Hadi

    Published 2021
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  5. 5
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  6. 6
    CNN architectures for road surface wetness classification from acoustic signals

    CNN architectures for road surface wetness classification from acoustic signals by Bahrami, Siavash, Doraisamy, Shyamala, Azman, Azreen, Nasharuddin, Nurul Amelina, Yue, Shigang

    “…The classification of road surface wetness is important for both the development of future driverless vehicles and the development of existing vehicle active safety systems. …”
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  7. 7
    Machine learning methods to predict and analyse unconfined compressive strength of stabilised soft soil with polypropylene columns

    Machine learning methods to predict and analyse unconfined compressive strength of stabilised soft soil with polypropylene columns by Hoque, Md. Ikramul, Muzamir, Hasan, Islam, Md Shofiqul, Houda, Moustafa, Abdallah, Mirvat, Sobuz, Md. Habibur Rahman

    Published 2023
    “…In addition, the sequential model got training loss of 0.2535, training accuracy of 0.9024, validation loss of 0.4056 and validation accuracy: 0.9091. …”
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  8. 8
    Real time self-calibration algorithm of pressure sensor for robotic hand glove system

    Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

    Published 2019
    “…This work shows that the Proposed model exhibited a remarkable performance than traditional methods with a max MSE of 0.17325 and R value over 0.99 for the total response of training, testing and validation. …”
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  9. 9
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
    thesis::doctoral thesis
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  10. 10
    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios

    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

    Published 2015
    “…In order to estimate daily evapotranspiration, daily observed Min and Max temperature was used in the estimation based on Hargreaves-Samani equation. …”
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  11. 11
    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease

    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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