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  1. 1
    Neural network paradigm for classification of defects on PCB

    Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

    Published 2003
    “…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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  2. 2
    Email spam classification based on deep learning methods: A review

    Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

    Published 2025
    “…The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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  3. 3
    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection

    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

    Published 2019
    “…To realize these objectives, the research in this thesis follows three basic stages, succeeded by extensive evaluations.…”
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    Thesis
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  4. 4
    A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features

    A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features by Keshkeh, Kinan, Jantan, Aman, Alieyan, Kamal

    Published 2022
    “…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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  5. 5
    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. The proposed EBrC-Net model is based on deep learning (DL) based approach. …”
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  6. 6
    Raspberry Pi-Based Finger Vein Recognition System Using PCANet

    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…Factors which impact PCANet are studied to identify the limitations of PCANet. For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. …”
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    Monograph
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  7. 7
    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…The following results were obtained when classification of the ACS types used the conventional “single AI-based” methods. …”
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  8. 8
    Simulation on Emotion Recognition for Autism Therapy

    Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

    Published 2017
    “…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. …”
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    Final Year Project
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  9. 9
    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
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  10. 10
    Satellite Image Segmentation Using Thresholding Technique

    Satellite Image Segmentation Using Thresholding Technique by Khalik, Mohd Haffez

    Published 2017
    “…Among all the segmentation techniques, thresholding segmentation method is the most popular algorithm and is widely used in the image segmentation field. …”
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  11. 11
    CYCLOSTATIONARY FEATURES BASED LOW COMPLEXITY MUTLIRESOLUTION SPECTRUM SENSING FOR COGNITVE RADIO APPLICATIONS

    CYCLOSTATIONARY FEATURES BASED LOW COMPLEXITY MUTLIRESOLUTION SPECTRUM SENSING FOR COGNITVE RADIO APPLICATIONS by Adoum, Bakhit Amine Adoum

    Published 2011
    “…Various multi resolution techniques are used that include wavelet based spectrum estimation and spectral hole detection, wavelet based multi-resolution in analog domain and multi-resolution multiple antenna based detection. …”
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  12. 12
    Malay continuous speech recognition using continuous density hidden Markov model

    Malay continuous speech recognition using continuous density hidden Markov model by Ting, Chee Ming

    Published 2007
    “…Hidden Markov Model (HMM) based statistical modeling is used in Malay speech recognition. …”
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  13. 13
    Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia

    Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia by Ju, Zeng, Tan, Mou Leong, Narimah Samat, Chang, Chun Kiat

    Published 2021
    “…This study aims to improve the land use mapping in a tropical region based on the GEE platform. …”
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  14. 14
    FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES

    FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES by MD HASIM, SITI MASTURA

    Published 2013
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    Final Year Project
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  15. 15
    Enhancement of neural network based multi agent system for classification and regression in energy system

    Enhancement of neural network based multi agent system for classification and regression in energy system by Yaw C.T., Yap K.S., Wong S.Y., Yap H.J., Paw J.K.S.

    Published 2023
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  16. 16
    Real-time oil palm fruit bunch ripeness grading system using image processing techniques

    Real-time oil palm fruit bunch ripeness grading system using image processing techniques by Alfatni, Meftah Salem M.

    Published 2013
    “…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
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  17. 17
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
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  18. 18
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  19. 19
    An adaptive ant colony optimization algorithm for rule-based classification

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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  20. 20
    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor

    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

    Published 2019
    “…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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    Undergraduate Final Project Report
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