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  1. 1
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, Norwati, Sulaiman, Md. Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2002
    “…Frequent pattern mining is a key problem in important data mining applications, such as the discovery of association rules, strong rules and episodes. Structure used in typical algorithms for solving this problem operate in several database scans and a large number of candidate generation. …”
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  2. 2
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, N., Sulaiman, M.N., Othman, M., Selamat, M.H.

    Published 2002
    “…Frequent pattern mining is a key problem in important data mining applications, such as the discovery of association rules, strong rules and episodes. Structure used in typical algorithms for solving this problem operate in several database scans and a large number of candidate generation. …”
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  3. 3
    A framework of rough cultural algorithms in optimizing mobile web caching performance

    A framework of rough cultural algorithms in optimizing mobile web caching performance by Sulaiman, Sarina, Shamsuddin, Siti Maryam, Abraham, Ajith, Sulaiman, Shahida

    Published 2007
    “…Consequently, The proposed caching scheme, Rough Cultural Algorithm (RCA) is developed to materialise the caching policies.…”
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  4. 4
    E-MyKad : An Online Identity Representation System for Malaysia’s Internet Community

    E-MyKad : An Online Identity Representation System for Malaysia’s Internet Community by Yusoff , Rizal

    Published 2013
    “…For many years, the online community in the world including Malaysia has increase dramatically. The people are using the internet mostly to interact and socialize with others and to do the online transactions such as selling and buying things. …”
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  5. 5
    Modelling semantic context for novelty detection in wildlife scenes

    Modelling semantic context for novelty detection in wildlife scenes by Yong, SP, Deng, JD, Purvis, MP

    Published 2010
    “…Working with wildlife image data, the framework starts with image segmentation, followed by feature extraction and classification of the image blocks extracted from image segments. …”
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  6. 6
    Analysis of minutia extraction techniques in fingerprint recognition.

    Analysis of minutia extraction techniques in fingerprint recognition. by Sudha Ponnarasi, S., Rajaram, M.

    Published 2012
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  7. 7
    Mel Frequency Cepstral Coefficient (MFCC) extraction for speaker identification on FPGA

    Mel Frequency Cepstral Coefficient (MFCC) extraction for speaker identification on FPGA by Phak Len, Eh Kan, Rafikha Aliana, Raof, Ahmad Nasir, Che Rosli, Razaidi, Hussin

    Published 2009
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  8. 8
    Extractive and Abstractive Sentence Labelling of Sentiment-bearing Topics

    Extractive and Abstractive Sentence Labelling of Sentiment-bearing Topics by Mohamad Hardyman, Barawi, Lin, Chenghua, Siddharthan, Advaith, Liu, Yinbing

    Published 2019
    “…The extractive approach uses a sentence ranking algorithm for label selection which for the first time jointly optimises topic-sentence relevance as well as aspect-sentiment co-coverage. …”
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  9. 9
    Kadazandusun speech recognition: a case study

    Kadazandusun speech recognition: a case study by Samry @ Mohd Shamrie Sainin, Mohd Hanafie Haris

    Published 2021
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  10. 10
    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli

    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

    Published 2017
    “…A few future recommendations such as Gray level co-occurrence matrix, Markov random field or Gabor filter to improve the feature extraction results. …”
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  11. 11
    A Preliminary Study of Wood Species Classifacation System Based on Wood Knot Texture Using K-Nearest Neighbour With Optimized Features From Binary Magnetic Optimization Algorithm Selection

    A Preliminary Study of Wood Species Classifacation System Based on Wood Knot Texture Using K-Nearest Neighbour With Optimized Features From Binary Magnetic Optimization Algorithm S... by Osman, Khairuddin, Mohamad, Syahrul Hisham, Jaafar, Hazriq Izzuan

    Published 2013
    “…The features of the wood knot images are extracted using Gray Level Co-Occurrence Matrix. Binary Magnetic Optimization Algorithm is use to optimize the feature selection process. …”
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  12. 12
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

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

    Published 2014
    “…The textural features extracted are based on the first-order statistics and second-order statistics computed from grey level co-occurrence matrices (GLCM). …”
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  13. 13
    Combining deep and handcrafted image features for MRI brain scan classification

    Combining deep and handcrafted image features for MRI brain scan classification by Hasan, Ali M., Jalab, Hamid A., Meziane, Farid, Kahtan, Hasan, Al-Ahmad, Ahmad Salah

    Published 2019
    “…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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  14. 14
    Image matching using relational graph representation

    Image matching using relational graph representation by Lai, Chui Yen

    Published 2005
    “…Structural descriptions are consist of lines and interline relationship in the line-extracted image. Three conditions of inter-line relationship, namely ordering, intersection and co-linearity, were defined and derived in this study. …”
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  15. 15
    An Approach for SARS-CoV-2 Infected Cases Report Analysis

    An Approach for SARS-CoV-2 Infected Cases Report Analysis by Tran, D.C., Ha, H.S., Nguyen, D.L., Ibrahim, R., Quach, L.D.

    Published 2020
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  16. 16
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…This algorithm was compared to co-spectral plot method for labelling clusters the clusters generated in Landsat TM dataset. …”
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  17. 17
    Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba

    Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba by Ghulam , Mujtaba

    Published 2018
    “…Moreover, support vector machines and random forest algorithms outperformed the four other algorithms. The proposed techniques are feasible and practical in determining the CoD from forensic autopsy reports and can assist pathologists to accurately and rapidly determine the CoD from autopsy findings. …”
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  18. 18
    Diabetic retinopathy detection using Gray-Level Co-Occurrence Matrix / Aliff Azfar Aris

    Diabetic retinopathy detection using Gray-Level Co-Occurrence Matrix / Aliff Azfar Aris by Aris, Aliff Azfar

    Published 2022
    “…To achieve this, the Gray-Level Co-Occurrence Matrix (GLCM) is used to extract features from fundus images of patients. …”
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  19. 19
    Developing stereo vision system for object recognition and positioning of AMAD-R mobile robot

    Developing stereo vision system for object recognition and positioning of AMAD-R mobile robot by Mohd Saifizi, Saidon, Hazry, Desa, Paulraj, Murugesa, Mohd Sofian, M. Rosbi

    Published 2009
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  20. 20
    Automatic classification of medical x-ray images

    Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

    Published 2013
    “…Image representation is one of the major aspects of automatic classification algorithms. In this paper, different feature extraction techniques have been utilized to represent medical X-ray images. …”
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