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  1. 1
    Computationally efficient sequential learning algorithms for direct link resource-allocating networks

    Computationally efficient sequential learning algorithms for direct link resource-allocating networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2005
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  2. 2
    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal

    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal by Camellia , Mohd Kamal

    Published 2004
    “…For Perception there will be the Description Neuron Model, Perceptron Basic Architecture and perceptron Algorithm with one example of solved problem. …”
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  3. 3
    A step towards the development of VHDL model for ANN based EMG signal classifier

    A step towards the development of VHDL model for ANN based EMG signal classifier by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
    “…A feed-forward ANN with back-propagation learning algorithm is used for the classification of EMG signals. …”
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  4. 4
    Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan

    Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

    Published 2024
    “…This paper proposes a sophisticated Job Position Prediction system utilizing Machine Learning algorithms and leveraging data from LinkedIn profiles. …”
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  5. 5
    Transfer Learning for Lung Nodules Classification with CNN and Random Forest

    Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

    Published 2023
    “…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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  6. 6
    Deep learning framework for hierarchical-based object identification and description

    Deep learning framework for hierarchical-based object identification and description by Alamro, Loai C. A.

    Published 2024
    “…In this study, a new DL framework called Human Identification and Description Framework (HIDF) is developed. The HIDF aims to overcome global generalization, hierarchical and correlation learning limitations by describing an object when it cannot be initially identified. …”
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  7. 7
    Transfer Learning for Lung Nodules Classification with CNN and Random Forest

    Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

    Published 2024
    “…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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  8. 8
    Text to Image Generation Using Machine Learning

    Text to Image Generation Using Machine Learning by Rishab, Tiwari, Chitra, K.

    Published 2024
    “…In order to solve this issue, we carried out a research work where we concentrated on developing the generative adversarial network (GAN), a deep learning-based architecture. …”
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  9. 9
    Digital economy tax compliance model in Malaysia using machine learning approach

    Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

    Published 2021
    “…Through a brief description of the descriptive model, the data distribution in a histogram shows that the information extracted can give a clear picture in influencing the results to classify digital economic tax compliance. …”
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  10. 10
    Factors and types of error that contributes to the difficulties in solving Mathematical problems among Year 5 pupils in SK Goebilt, Kuching / Hardi Rasidi

    Factors and types of error that contributes to the difficulties in solving Mathematical problems among Year 5 pupils in SK Goebilt, Kuching / Hardi Rasidi by Rasidi, Hardi

    Published 2016
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  11. 11
    Customer mobile behavioral segmentation and analysis in telecom using machine learning

    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
    “…Unsupervised machine learning algorithm K-means was used to cluster the data, and these results were analyzed and labeled with labels and descriptions. …”
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  12. 12
    Identifying living organisms by using artificial neural networks approach / Raifiza Abdul Rahim

    Identifying living organisms by using artificial neural networks approach / Raifiza Abdul Rahim by Abdul Rahim, Raifiza

    Published 2003
    “…Artificial neural network (ANN), which is one of the commonly used machine learning technique, might be preferable to form its own descriptions of genetic concepts. …”
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  13. 13
    A Fusion-Based Framework For Explainable Suicide Attempt Prediction

    A Fusion-Based Framework For Explainable Suicide Attempt Prediction by Nordin, Noratikah

    Published 2024
    “…The proposed work aims to analyse an explainable learning algorithms for predicting suicide attempts, propose an ontology model for semantically representing the classification risk of suicide attempts and propose an explanation generation algorithm by combining predictions from explainable machine learning and ontology models. …”
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  14. 14
    Statistics Easy Tool (SET) / Noor Aisyah Idris and Nurdia Azlin Ghazali

    Statistics Easy Tool (SET) / Noor Aisyah Idris and Nurdia Azlin Ghazali by Idris, Noor Aisyah, Ghazali, Nurdia Azlin

    Published 2021
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  15. 15
    Current applications of machine learning in dentistry

    Current applications of machine learning in dentistry by Ghazali, Ahmad Badruddin, Reduwan, Nor Hidayah, Ibrahim, Roliana

    Published 2022
    “…Machine learning (ML), a subset of AI was described as an algorithm with the ability to "learn" by identifying patterns in a large dataset (Rowe, 2019). …”
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  16. 16
    Unsupervised place recognition for assistive mobile robots based on local feature descriptions.

    Unsupervised place recognition for assistive mobile robots based on local feature descriptions. by Tang, Sai Hong, Ramli, Abdul Rahman, Samsudin, Khairulmizam

    Published 2011
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  17. 17
    Artificial Intelligence Integration in Mobile Applications: Innovation and Challenges in Supporting Quran Memorization and Review

    Artificial Intelligence Integration in Mobile Applications: Innovation and Challenges in Supporting Quran Memorization and Review by Khairulnazrin Nasir, Rahim Kamarul Zaman, Ahmad Bazli Ahmad Hilmi, Abdul Hakim Mahadzir, Ahmad Mukhlis bin Mustaffa

    Published 2025
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  18. 18
    Framework development in extracting rules from trained neural network / Shuzlina Abdul Rahman, Azlinah Hj Mohamed and Marina Yusoff

    Framework development in extracting rules from trained neural network / Shuzlina Abdul Rahman, Azlinah Hj Mohamed and Marina Yusoff by Abdul Rahman, Shuzlina, Mohamed (Hj), Azlinah, Yusoff, Marina

    Published 2006
    “…In addressing this framework, the criteria of each approaches has been explored and analyzed from eight factors: process extraction, merit, demerit, rule type, type of data, rule quality, processing complexity, and the description of each RE technique. The analysis is derived by excavating literature on RE techniques starting from the year 1993 until 2003 focused on supervised learning algorithm. …”
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    Research Reports
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  19. 19
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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  20. 20
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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