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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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    Thesis
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  8. 8
    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
    “…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    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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  14. 14
    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, N.F.B., Faye, I., May, Z.

    Published 2014
    “…A working classification algorithm is developed and gives a mean accuracy of 84 out of 125 test images. …”
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  15. 15
    Overview of biomedical relations extraction using hybrid rule-based approaches.

    Overview of biomedical relations extraction using hybrid rule-based approaches. by Abdul Kadir, Rabiah, Bokharaeian, Behrouz

    Published 2013
    “…There are many variants of these algorithms have been developed but the combination of it has not been verified yet. …”
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  16. 16
    Development and application of an enhanced ART-Based neural network

    Development and application of an enhanced ART-Based neural network by Keem, Siah Yap, Chee, Peng Lim, W.M Lee, Eric, Junita, Mohamed Saleh

    Published 2009
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  17. 17
    Development of interactive application for classification of Artocarpus Species

    Development of interactive application for classification of Artocarpus Species by Abdul Ghapar, Nadia

    Published 2020
    “…The combination of Prewitt algorithm, Canny alogorithm, Gray-Level co-occurrence matrix will be used in SVM. …”
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    Undergraduate Final Project Report
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  18. 18
    Engine fault diagnosis using probabilistic neural network

    Engine fault diagnosis using probabilistic neural network by Sheng, Zhu, Min, Keng Tan, Ka, Renee Yin Chin, Bih, Lii Chua, Xiaoxi, Hao, Tze, Kenneth Kin Teo

    Published 2021
    “…A benchmarked engine fault model is developed and simulated in Maltab. The proposed algorithm is designed to detect 9 common engine faults based on the information extracted from exhaust gas, such as hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), carbon dioxide (CO2) and dioxygen (O2). …”
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  19. 19
    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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  20. 20
    Image quality assessment using Elman neural network model

    Image quality assessment using Elman neural network model by Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Palaniappan, Rajkumar, Mohd Shuhanaz, Zanar Azalan

    Published 2012
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