Search Results - (( pattern detection method algorithm ) OR ( data visualization using algorithm ))

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  1. 1

    Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

    Published 2022
    “…Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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    Academic Exercise
  2. 2

    Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi by Mohd Pauzi, Mohd Farhan

    Published 2022
    “…This problem occurs due to lacking of existing system in detecting children image in a car. Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. …”
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    Thesis
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    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
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    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  6. 6

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  7. 7

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  8. 8

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  9. 9

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  10. 10

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…Automated system also saves time and cost as the system is able to process large amount of image data at one time. This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Final Year Project
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    Enhancing data integrity in internet of things-based healthcare applications: a visualization approach for duplicate detection by Md Isa, Siti Noor Basirah, Emran, Nurul Akmar, Harum, Norharyati, Logenthiran, Machap, Nordin, Azlin

    Published 2025
    “…However, scalability limitations were observed in larger datasets, where visual clarity declined. These findings highlight the value of visualization as a preliminary data quality assessment tool and suggest future integration with advanced detection algorithms to enhance robustness and scalability…”
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    Article
  13. 13

    P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

    Published 2012
    “…In this research the BCI competition data-set has been processed through 5 optimized detection methods. …”
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    Thesis
  14. 14

    Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

    Published 2018
    “…This paper proposes an effective algorithm of texture analysis based on novel technique using Gray Level Co-occurrence Matrix approach to be applied so as to identify blood-flow region. …”
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    Article
  15. 15

    Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis by Siti Nur Hidayah, Mazelan

    Published 2022
    “…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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    Undergraduates Project Papers
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    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
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    Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation by Liaghat, Shohreh

    Published 2013
    “…The limitations of current detection technique have led to an interest in developing alternative field-based methods that can be used for rapid diagnosis of this disease. …”
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    Thesis
  20. 20

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph