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  1. 1

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Firstly is by enhancing the learning algorithm of a neural-fuzzy network; and secondly by devising an ensemble model to combine the predictions from multiple neural-fuzzy networks using an agent-based framework. …”
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    Thesis
  2. 2

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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    Thesis
  3. 3

    Lambda-Max neuro-fuzzy system / Nurul Adzlyana Mohd. Saadon by Mohd. Saadon, Nurul Adzlyana

    Published 2013
    “…The newly developed Lambda-Max ANFIS is then used to predict the physical properties of degradable plastics using real life data obtained from the laboratory of the Malaysian Palm Oil Board (MPOB). …”
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    Thesis
  4. 4
  5. 5

    ANALYSIS OF BIOSENSOR PHYSIOLOGICAL SIGNALS FOR ASSESSMENT OF NEUROLOGICAL STATUS by QIAN XIN, SOONG

    Published 2018
    “…The extracted features are then fed into the Support Vector Machines (SVM) as well as the Ensemble Classifier which is a supervised learning model with associated learning algorithm that helps us to analyze the data for classification of neurological status of the subjects. …”
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    Final Year Project
  6. 6

    Lambda-max criteria weight determination in an adaptive neuro-fuzzy inference system / Rosma Mohd Dom, Daud Mohamad and Ajab Bai Akbarally by Mohd Dom, Rosma, Mohamad, Daud, Akbarally, Ajab Bai

    Published 2012
    “…A neuro-fuzzy system is a fuzzy system that uses learning algorithms derived from or inspired by neural network theory to determine its parameters (fuzzy sets and fuzzy rules) by processing data samples. …”
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    Research Reports
  7. 7

    Comparative Analysis of Pneumonia Detection from Chest X-Ray Images Using CNN And Transfer Learning by Naveen Kumar, M., Ushasree, ., Che Fuzlina, Fuad

    Published 2024
    “…Keywords: Pneumonia, Chest X-ray, Deep Learning, Convolutional Neural Network (CNN), Mobile Net, VCG, ReLU, Max pooling.…”
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    Article
  8. 8

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

    Published 2022
    “…Nowadays, there are numerous license plate recognition systems that have been developed and analysed effectively by previous researchers using different machine learning algorithms. …”
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    Student Project
  9. 9
  10. 10

    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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    Article
  11. 11

    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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    Conference or Workshop Item
  12. 12

    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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    Conference or Workshop Item
  13. 13
  14. 14

    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
    “…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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    Thesis