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  1. 1
    Non-invasive pathological voice classifications using linear and non-linear classifiers

    Non-invasive pathological voice classifications using linear and non-linear classifiers by Hariharan, Muthusamy

    Published 2010
    “…Two types of experiments are conducted using the proposed feature extraction and classification algorithms. …”
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    Thesis
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  2. 2
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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    Monograph
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  3. 3
    Detection of acute leukaemia cells using variety of features and neural networks

    Detection of acute leukaemia cells using variety of features and neural networks by A. S., Abdul Nasir, Mohd Yusoff, Mashor, Prof. Dr., H., Rosline

    Published 2011
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  4. 4
    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons

    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

    Published 2020
    “…The issue has been extensively addressed in uncountable researches and using various techniques, of which a commonly used technique is that based on detecting intrusions in contrast to normal network traffic and the classification of network packets as either normal or abnormal. …”
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  5. 5
    Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach

    Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach by Sumiati, ., Hoga, Saragih, T.K.A, Rahman, Viktor Vekky, Ronald Repi, Agung, Triayudi

    Published 2021
    “…In this article, the classification of cardiac abnormalities from electrocardio�gram medical data has been carried out using the Fuzzy Cognitive Map (FCM) approach. …”
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  6. 6
    Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / Mohamad Firdaus Mohamad Salehuddin

    Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / Mohamad Firdaus Mohamad Salehuddin by Mohamad Salehuddin, Mohamad Firdaus

    Published 2020
    “…For both cases, the statistical analysis data show that the p-value is more than 0.05, which indicates that the data are normally distributed. These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. …”
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    Student Project
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  7. 7
    Detection of corneal arcus using rubber sheet and machine learning methods

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The classification algorithms such as the Lavenberg-Marquardt (LM), Bayesian regularization (BR), scaled conjugate gradient (SCG) and one model of bag-of-features (BoF) are used in this research. …”
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    Thesis
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  8. 8
    An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks

    An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

    Published 2020
    “…Many algorithms have been developed for automated electrocardiogram (ECG) classification. …”
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  9. 9
    Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter

    Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter by Tengku Azis, Tengku Mohd Syamim

    Published 2015
    “…One of the main processing technique in CAD is texture classification and analysis. In this research, a Gabor-based emphysema classification algorithm is proposed. …”
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    Final Year Project
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  10. 10
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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  11. 11
    Symmetric Key Size for Different Level of Information Classification

    Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

    Published 2006
    “…Therefore confidential information is normally protected by using cryptographic algorithms. …”
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  12. 12
    Classification of Rheumatoid Arthritis using Machine Learning Algorithms

    Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

    Published 2019
    “…Furthermore, this database which consists of 8 attributes and 32 instances, are used to determine the performance in terms of accuracy for the classification of different algorithms. …”
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  13. 13
    Classification of Rheumatoid Arthritis using Machine Learning Algorithms

    Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

    Published 2019
    “…Furthermore, this database which consists of 8 attributes and 32 instances, are used to determine the performance in terms of accuracy for the classification of different algorithms. …”
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  14. 14
    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…The proposed TWOA achieved a higher fault classification result of 99.98% compared to other algorithms.…”
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  15. 15
    Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image

    Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

    Published 2016
    “…The classification accuracy using spectral indices were compared with the normal supervised pixel-based classification of SVM. …”
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  16. 16
    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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  17. 17
    Identification of vocal and voice disorders

    Identification of vocal and voice disorders by Murugesa Pandiyan, Paulraj, Prof. Madya Dr., Sazali, Yaacob, Prof. Dr., Mohd Rizon, Mohammed Juhari, Prof. Dr., Sivanandam, S. N., Muthusamy, Hariharan, Dr.

    Published 2011
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  18. 18
    Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms

    Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms by Haw, Jia Yong, Mohd Yousof, Mohd Fairouz, Abd Rahman, Rahisham, Talib, Mohd Aizam, Azis, Norhafiz

    Published 2022
    “…However, there are times where the produce of stray gassing event might lead to fault indication in the transformer. Machine learning algorithms are used to classify the DGA data into normal condition and corresponding faults based on IEEE limits and Duval pentagon method. …”
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    Article
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  19. 19
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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  20. 20
    AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION

    AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION by LAW, JIN MING

    Published 2022
    “…This project aims to construct an autonomous power line inspection system using computer vision to classify and localise the normal and abnormal insulators. …”
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    Final Year Project Report / IMRAD
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