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  1. 1
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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  2. 2
    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar

    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

    Published 2020
    “…The information of building features especially in the urban area is very important to support urban management and development. Nevertheless, the automated and transferable detection of building features is still challenging because of variations of the spatial and spectral characteristics to support urban building classification using remote sensing techniques. …”
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  3. 3
    Feedforward neural network for solving particular fractional differential equations

    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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  4. 4
    Improving robotic grasping system using deep learning approach

    Improving robotic grasping system using deep learning approach by Mohannad K. H., Farag

    Published 2020
    “…This research aimed to develop a Deep Learning grasp detection model and a slip detection algorithm and integrating them into one innovative robotic grasping system. …”
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  5. 5
    Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli

    Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli by Mohd Ramli, Mohamad Amirul Asyraf

    Published 2023
    “…By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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    Student Project
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  6. 6
    Study of machine learning in computer vision using Raspberry Pi

    Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

    Published 2024
    text::Final Year Project
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  7. 7
    A review of Convolutional Neural Networks in Remote Sensing Image

    A review of Convolutional Neural Networks in Remote Sensing Image by Liu, Xinni, Han, Fengrong, Kamarul Hawari, Ghazali, Izzeldin, I. Mohd, Zhao, Yue

    Published 2019
    “…Recently, convolutional neural network based deep learning algorithm has achieved a series of breakthrough research results in the fields of objective detection, image semantic segmentation and image classification, etc. …”
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    Conference or Workshop Item
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  8. 8
    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction

    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

    Published 2021
    “…Due to this developing significance of crop yield prediction, this article provides an exhaustive review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction. …”
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  9. 9
    Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment

    Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment by Yekeen, S.T., Balogun, A.-L.

    Published 2020
    “…On the other hand, deep learning modelsâ�� strong feature extraction and autonomous learning capability enhance their detection accuracy. …”
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  10. 10
    HandGestureSense: Hand gesture recognition-controlled smart home automation

    HandGestureSense: Hand gesture recognition-controlled smart home automation by Tan, Teck Sheng

    Published 2024
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    Final Year Project / Dissertation / Thesis
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  11. 11
    HandGestureSense: Hand gesture recognition-controlled smart home automation

    HandGestureSense: Hand gesture recognition-controlled smart home automation by Tan, Teck Sheng

    Published 2024
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  12. 12
    Spatiotemporal extraction of aquaculture ponds under complex surface conditions based on deep learning and remote sensing indices

    Spatiotemporal extraction of aquaculture ponds under complex surface conditions based on deep learning and remote sensing indices by Qin, Weirong, Ismail, Mohd Hasmadi, Ramli, Mohammad Firuz, Deng, Junlin, Wu, Ning

    Published 2025
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  13. 13
    A novel deep learning instance segmentation model for automated marine oil spill detection

    A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

    Published 2020
    “…So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. …”
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  14. 14
    A novel deep learning instance segmentation model for automated marine oil spill detection

    A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

    Published 2020
    “…So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. …”
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  15. 15
    Earthquake prediction model based on geomagnetic field data using automated machine learning

    Earthquake prediction model based on geomagnetic field data using automated machine learning by Yusof, Khairul Adib, Mashohor, Syamsiah, Abdullah, Mardina, Amiruddin, Mohd, Rahman, Abd, Abdul Hamid, Nurul Shazana, Qaedi, Kasyful, Matori, Khamirul Amin, Hayakawa, Masashi

    Published 2024
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  16. 16
    Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm

    Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

    Published 2010
    “…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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    Citation Index Journal
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  17. 17
    Estimating Forest Aboveground Biomass Density Using Remote Sensing and Machine Learning : A RSME Approach

    Estimating Forest Aboveground Biomass Density Using Remote Sensing and Machine Learning : A RSME Approach by Yaniza Shaira, Zakaria, Mohd Fadzil, Akhir, Aidy, M Muslim, Nur Afiqah, Ariffin, Azizul, Ahmad

    Published 2025
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  18. 18
    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
    “…It also has glossary that gives sense to certain new words in the next. In providing convenience to users, this system is developed as a stand-alone application. …”
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  19. 19
    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
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  20. 20
    Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets

    Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets by Adedayo, Ojo O., Mohd Isa, Maryam, Che Soh, Azura, Abbas, Zulkifly

    Published 2014
    “…The ANN training data were obtained from Open-ended Coaxial Probe (OCP) microwave measurements and the quasi-static admittance model, the ANN was trained with four different training algorithms: Levenberg Marquardt (LM) algorithm, Gradient Descent with Momentum (GDM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA) algorithm. …”
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