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  1. 1
    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga

    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…At the same time, there has been growing interest from the research community in machine learning based detection of diseases using sequence based on gut microbiome data. …”
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  2. 2
    An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles

    An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles by Muhammad Qasim, Khan, Musse Mohamud, Ahmed, Ahmed Mohamed, Ahmed Haidar

    Published 2022
    “…The algorithm includes an index for faulty bus classification based on the positive-sequence voltage measurements of the pre-fault and post-fault conditions, where the bus with a maximum differential percentage is identified as a faulted bus. …”
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  3. 3
    Classification and detection of intelligent house resident activities using multiagent

    Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

    Published 2013
    “…The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. …”
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  4. 4
    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm

    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

    Published 2020
    “…Experimental results show that there are reasonable and efficient to combine classic object detection method with a deep learning classification approach. …”
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  5. 5
    Integrating Pixel-Based Algorithms for Area Measurement in Brain Tumor Classification

    Integrating Pixel-Based Algorithms for Area Measurement in Brain Tumor Classification by Dwi Swasono, Rachmad

    Published 2025
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  6. 6
    Electroencephalogram (EEG)-based systems to monitor driver fatigue: a review

    Electroencephalogram (EEG)-based systems to monitor driver fatigue: a review by Kamat, Seri Rahayu, Ibrahim, Muhammad Shafiq, Shamsuddin, Syamimi, Md Isa, Mohd Hafzi, Ito, Momoyo

    Published 2022
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  7. 7
    ANALYSIS OF CLASSIFICATION PROCESS FOR VIDEO SCENE UNDERSTANDING

    ANALYSIS OF CLASSIFICATION PROCESS FOR VIDEO SCENE UNDERSTANDING by MOHD RASHDAN, NURUL FARAH

    Published 2019
    “…In the frame process, important information will be extracted from the video images accordance to frame sequence where Spatial Temporal -Interest-Point (STIP) is used based on Harris’ Corner detection. …”
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    Final Year Project
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  8. 8
    Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning

    Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning by Goh, Ching Pang

    Published 2023
    “…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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  9. 9
    Convolutional neural networks with feature fusion method for automatic modulation classification

    Convolutional neural networks with feature fusion method for automatic modulation classification by Elshebani, Mohamed Salem, Ali, Yahya, Azroug, Nser, Khalifa, Ramdan A. M., Khalifa, Othman Omran, Saeed, Rashid A.

    Published 2023
    “…However, most existing modulation classification algorithms are neglecting the fact of mixing features between different representations, and the importance of features fusion method. …”
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  10. 10
    A fuzzy approach for early human action detection / Ekta Vats

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…Most existing methods deal with the detection of an action after its completion. …”
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  11. 11
    A study on component-based technology for development of complex bioinformatics software

    A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

    Published 2004
    “…Othman present a comprehensive method based on two-layer multiclass classifiers. …”
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    Monograph
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  12. 12
    Detection and Classification of Moving Objects for an Automated Surveillance System

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  13. 13
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  14. 14
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  15. 15
    Recognition system for leaf images based on its leaf contour and centroid

    Recognition system for leaf images based on its leaf contour and centroid by Mohamed Khmag, Asem Ib., Syed Mohamed, Syed Abdul Rahman Al-Haddad, Kamarudin, Noraziahtulhidayu

    Published 2017
    “…The leaf contours of the same plants are computed using Support Victor Machine (SVM) where the similar sequences of the same contours usually carry the same features while the different plants sequences have different contours. …”
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  16. 16
    Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images

    Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

    Published 2025
    “…This study presents a computer-aided diagnosis (CAD) system designed to detect and classify stroke lesions in magnetic resonance imaging (MRI), specifically utilizing diffusion-weighted imaging (DWI) sequences. …”
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  17. 17
    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
    “…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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  18. 18
    Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan

    Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan by Roslan, Rosniza

    Published 2013
    “…A new double thresholding algorithm and a fully automated multiple seed points selection algorithm that works on all three MRI image sequences are also proposed. …”
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  19. 19
    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification

    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

    Published 2024
    “…Recently, the swarm-based hybrid algorithms have given significant performance in cancer classification. …”
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  20. 20
    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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