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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
    “…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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  2. 2
    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images

    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images by Jabar F.H.A., Ismail W., Salam R.A., Hassan R.

    Published 2024
    Conference Paper
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  3. 3
    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 will apply various clustering algorithms to analyzed and determine every attribute in the dataset structure pattern. …”
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  4. 4
    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
    “…Result shows that, the algorithm can successfully identify 135 unique tasks of different lengths.This algorithm is surely being an alternate way of pattern recognition in intelligent home.…”
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  5. 5
    Detection of tube defect using the autoregressive algorithm

    Detection of tube defect using the autoregressive algorithm by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. …”
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  6. 6
    Evaluation of intonation features on emphasized Malay words / Syazwani Nasaruddin

    Evaluation of intonation features on emphasized Malay words / Syazwani Nasaruddin by Nasaruddin, Syazwani

    Published 2017
    “…The pattern of the features such as intensity and pitch are observed and clustered to find out how many patterns can be identified from all the words. …”
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  7. 7
    Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection

    Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…The signals were then clustered using the feature extraction algorithms. …”
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  8. 8
    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana

    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

    Published 2018
    “…Anomaly-based Intrusion Detection System (IDS) uses known baseline to detect patterns which have deviated from normal behaviour. …”
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  9. 9
    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
    “…Clustering is one of the promising techniques used in Anomaly Intrusion Detection (AID), especially when dealing with unknown patterns. …”
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  10. 10
    Detecting lung cancer region from CT image using meta-heuristic optimized segmentation approach

    Detecting lung cancer region from CT image using meta-heuristic optimized segmentation approach by Shakeel, Pethuraj Mohamed, Mohd Aboobaider, Burhanuddin, Salahuddin, Lizawati

    Published 2022
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  11. 11
    Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images

    Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images by Jabar, FHA, Ismail, W, Salam, RA, Hassan, R

    Published 2024
    Proceedings Paper
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  12. 12
    Application of kohonen neural network and rough approximation for overlapping clusters optimization

    Application of kohonen neural network and rough approximation for overlapping clusters optimization by Mohebi, E., Md. Sap, Mohd. Noor

    Published 2008
    “…Experiments show that the proposed two-level algorithm is more accurate and generates fewer errors as compared with crisp clustering operations.…”
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  13. 13
    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications

    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

    Published 2022
    “…Without human input, these algorithms discover patterns or groupings in the data. …”
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  14. 14
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  15. 15
    Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network

    Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network by Sama, Najm Us

    Published 2019
    “…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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  16. 16
    Identifying multiple outliers in linear functional relationship model using a robust clustering method

    Identifying multiple outliers in linear functional relationship model using a robust clustering method by Adilah Abdul Ghapor, Yong Zulina Zubairi, Al Mamun, Sayed Md., Siti Fatimah Hassan, Elayaraja Aruchunan, Nurkhairany Amyra Mokhtar

    Published 2023
    “…Outliers are some observation points outside the usual pattern of the other observations. It is essential to detect outliers as anomalous observations can affect the inference made in the analysis. …”
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  17. 17
    Low area Programmable Memory Built-In Self-Test (PMBIST) for small embedded ram cores / Nur Qamarina Mohd Noor

    Low area Programmable Memory Built-In Self-Test (PMBIST) for small embedded ram cores / Nur Qamarina Mohd Noor by Mohd Noor, Nur Qamarina

    Published 2013
    “…The first experiment is performed by clustering test patterns of RAMs under test. The second experiment deeply encodes the clusters of test patterns to improve the cluster technique to allow multiple test data types. …”
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  18. 18
    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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  19. 19
    A Distributed Event Detection Scheme for Wireless Sensor Networks

    A Distributed Event Detection Scheme for Wireless Sensor Networks by Muhamad Amin , Anang Hudaya, Khan, Asad I., Raja Mahmood, Raja Azlina

    Published 2009
    “…Many of the existing event detection schemes in wireless sensor networks that employ classification or clustering approaches suffer from high communication and computational overheads. …”
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  20. 20
    Anomaly detection of intrusion based on integration of rough sets and fuzzy c-means

    Anomaly detection of intrusion based on integration of rough sets and fuzzy c-means by Chimphlee, Witcha, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Chimphlee, Siriporn

    Published 2005
    “…We are using a Rough Sets to select a subset of input features for clustering with a goal of increasing the detection rate and decreasing the false alarm rate in network intrusion detection. …”
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