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  1. 1
    Object detection system using haar-classifier

    Object detection system using haar-classifier by Wan Najwa, Wan Ismail

    Published 2009
    “…An algorithm for the design object detection systems is presented. …”
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    Undergraduates Project Papers
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  2. 2
    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin

    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

    Published 2022
    “…The Windows malware dataset has been trained and tested by these three machine learning algorithms to get the percentage detection accuracy. …”
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    Student Project
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  3. 3
    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm

    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
    “…Proposed real-time training dataset for SVM algorithm achieved highest detection rate of 99.13% while decision tree and Naïve Bayes has 93.28% & 86.41% of attack detection rate, respectively. …”
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  4. 4
    Development of vehicle detection and counting system for traffic analysis using computer vision

    Development of vehicle detection and counting system for traffic analysis using computer vision by Saw, Kenny Wei Wen

    Published 2024
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    Final Year Project / Dissertation / Thesis
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  5. 5
    Neural network algorithm-based fall detection modelling

    Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

    Published 2020
    “…High recognition of developed fall detection model is very significance for the elderly to detect the falls. …”
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  6. 6
    Development of intrusion detection system using residual feedforward neural network algorithm

    Development of intrusion detection system using residual feedforward neural network algorithm by Rustam, Rushendra, Ramli, Kalamullah, Hayati, Nur, Ihsanto, Eko, Gunawan, Teddy Surya, Halbouni, Asmaa Hani

    Published 2022
    “…The RFNN algorithm is developed to avoid overfitting, improve detection accuracy, and accelerate training and inference. …”
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    Proceeding Paper
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  7. 7
    Using streaming data algorithm for intrusion detection on the vehicular controller area network

    Using streaming data algorithm for intrusion detection on the vehicular controller area network by Sharmin, Shaila, Mansor, Hafizah, Abdul Kadir, Andi Fitriah, Abdul Aziz, Normaziah

    Published 2022
    “…The size of the training sample is, however, found to be an important consideration - a model trained with only 30 s of CAN traffic always yields better detection performance than a model trained with a larger window of CAN traffic.…”
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  8. 8
    Mobile machine vision for railway surveillance system using deep learning algorithm

    Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

    Published 2021
    “…In this paper, object detection model is developed and implemented with deep learning algorithm. …”
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    Proceedings
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  9. 9
    Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection

    Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection by Muhammad Arif, Mohamad, Muhammad Aliif, Ahmad, Zuriani, Mustaffa

    Published 2024
    “…There are multiple techniques in training the network, one of which is training with metaheuristic algorithms. …”
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  10. 10
    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin

    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

    Published 2024
    “…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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  11. 11
    Machine learning algorithms in context of intrusion detection

    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…Many machine learning techniques have been developed to cope with this problem. These machine learning algorithms develop a detection model in a training phase. …”
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  12. 12
    Detection Of Misplaced And Missing Regions In Image Using Neural Network

    Detection Of Misplaced And Missing Regions In Image Using Neural Network by Tan , Jin Siang

    Published 2017
    “…Therefore, it is necessary to develop an algorithm that is able to detect both misplaced and missing jigsaw puzzles. …”
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    Thesis
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  13. 13
    Extended development of a Computer Aided Detection (CAD) system for brain bleed in CT / Muhammad Illyas Abdul Muhji

    Extended development of a Computer Aided Detection (CAD) system for brain bleed in CT / Muhammad Illyas Abdul Muhji by Muhammad Illyas, Abdul Muhji

    Published 2018
    “…Final output of the algorithm summarise the bleeding detection for all patient in an excel file. …”
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  14. 14
    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen

    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen by Panagen, Suriyanti

    Published 2006
    “…Knowledge appearance is compulsory for neural network in which it comes under the training phase before it recognize or detecting any pattern.A study about the artificial neural network has been done and back propagation training algorithm is suitable for this system development. …”
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  15. 15
    DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES

    DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES by HANIZAM, MOHD HAZIQ NAZMI

    Published 2019
    “…The implementation of the algorithm consists of three stages which are pre-processing, network training and accuracy evaluation. …”
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    Final Year Project
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  16. 16
    Vehicle Detection in Deep Learning

    Vehicle Detection in Deep Learning by Teoh, Per Nian

    Published 2019
    “…With the development of computer vision techniques and accessibility of large-scale traffic transport data, deep learning has been enabled to on-road vehicle detection algorithms. …”
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  17. 17
    Early detection of dengue disease using extreme learning machine

    Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

    Published 2018
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  18. 18
    Early tube leak detection system for steam boiler at KEV power plant

    Early tube leak detection system for steam boiler at KEV power plant by Ismail F.B., Singh D., Maisurah N., Musa A.B.B.

    Published 2023
    Conference Paper
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  19. 19
    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
    “…Thus, this research is aimed to develop two models. First, the BrC detection model is developed to diagnose BrT basic types like benign and malignant. …”
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  20. 20
    Development of a detection and classification method for induction motor faults using Motor Current Signature Analysis and Feedforward Neural Network / Felicity Bulan Leo Uchat

    Development of a detection and classification method for induction motor faults using Motor Current Signature Analysis and Feedforward Neural Network / Felicity Bulan Leo Uchat by Leo Uchat, Felicity Bulan

    Published 2016
    “…As it is important to choose proper training algorithm for training the FNN, therefore three different FNN training algorithms are compared in terms of their accuracy, number of iterations and training time.…”
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