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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis

    Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

    Published 2021
    “…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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    Monograph
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  3. 3
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    Book
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  4. 4
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…However, the MBGWO has several issues in finding a good quality solution. Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
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  5. 5
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  6. 6
    Random Undersampling on Imbalance Time Series Data for Anomaly Detection

    Random Undersampling on Imbalance Time Series Data for Anomaly Detection by Saripuddin M., Suliman A., Syarmila Sameon S., Jorgensen B.N.

    Published 2023
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  7. 7
    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column

    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column by Othman, M. R., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2003
    “…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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  8. 8
    A Simple Yet Reliable Facial Emotion Detection For Campus Environment

    A Simple Yet Reliable Facial Emotion Detection For Campus Environment by Amar Lokman, Mus’ab Sahrim, Wan Zakiah Wan Ismail, Sharma Rao Balakrishnan, Juliza Jamaludin

    Published 2024
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  9. 9
    Artificial immune system based on real valued negative selection algorithms for anomaly detection

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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  10. 10
    Outbreak detection model based on danger theory

    Outbreak detection model based on danger theory by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

    Published 2014
    “…In outbreak detection, one of the key issues is the need to deal with the weakness of early outbreak signals because this causes the detection model to have has less capability in terms of robustness when unseen outbreak patterns vary from those in the trained model. …”
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  11. 11
    EEG-based fatigue detection using binary pattern analysis and KNN algorithm

    EEG-based fatigue detection using binary pattern analysis and KNN algorithm by Abd Rahman, Faridah, Roslizan, Iszan Uwais Amer, Gunawan, Teddy Surya, Fitriawan, Helmy, Kartiwi, Mira, Habaebi, Mohamed Hadi

    Published 2024
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  12. 12
    Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki

    Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

    Published 2024
    “…The dyslexia handwriting detection prototype demonstrates how machine learning may improve the detect handwriting issues in educational settings. …”
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  13. 13
    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System

    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by R.Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

    Published 2019
    “…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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  14. 14
    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System

    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

    Published 2019
    “…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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  15. 15
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…Today, many real issues and scenarios require pattern recognition to aid in the faster resolution of complicated problems, particularly those that cannot be solved using traditional human heuristics. …”
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  16. 16
    An improved artificial dendrite cell algorithm for abnormal signal detection

    An improved artificial dendrite cell algorithm for abnormal signal detection by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak, Abdul Wahab, Mohd Helmy

    Published 2018
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  17. 17
    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system

    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…Recently, researchers suggested a deep belief network (DBN) algorithm to construct and build a network intrusion detection system (NIDS) for detecting attacks that have not been seen before. …”
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  18. 18
    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling

    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

    Published 2011
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  19. 19
    A COMBINED HISTOGRAM OF ORIENTED GRADIENTS AND COMPLETED LOCAL BINARY PATTERN METHODS FOR PEOPLE COUNTING IN A DENSE CROWD SCENARIO

    A COMBINED HISTOGRAM OF ORIENTED GRADIENTS AND COMPLETED LOCAL BINARY PATTERN METHODS FOR PEOPLE COUNTING IN A DENSE CROWD SCENARIO by PARDIANSYAH, INDRATNO

    Published 2016
    “…This method used a collaborative Histogram of Oriented Gradients (HOG) and Completed Local Binary Pattern (CLBP) based on people detection algorithm to detect headshoulder region. …”
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  20. 20
    RFID-enabled supply chain detection using clustering algorithms

    RFID-enabled supply chain detection using clustering algorithms by Azahar, T.F., Mahinderjit-Singh, M., Hassan, R.

    Published 2015
    “…We propose to use clustering algorithms in order to detect counterfeit in supply chain management. …”
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