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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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  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
    Sensing texture using an artificial finger and a data analysis based on the standard deviation

    Sensing texture using an artificial finger and a data analysis based on the standard deviation by Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, Nik Hazrin, Cranny, Andy, White, Neil M.

    Published 2015
    “…The results from experiments with a screen-printed piezoelectric sensor, mounted on an artificial finger-tip and including a cosmetic covering, are shown to detect surface information from regular texture patterns. For the automatic control of an artificial hand and to feedback information to the amputee, an algorithm has been developed based on the standard deviation (SD) of signal data from the sensor. …”
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  6. 6
    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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  7. 7
    Haptic Texture Search Engine Framework

    Haptic Texture Search Engine Framework by Adi, Waskito, Sulaiman, Suziah

    Published 2010
    “…Based on our experiments that include searching algorithm and haptic rendering, the result shows that computer vision algorithm can be applied into and suitable for generating haptic textures. …”
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  8. 8
    Sensing texture using an artificial finger and a data analysis based on the standard deviation

    Sensing texture using an artificial finger and a data analysis based on the standard deviation by Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, N. H. H, Cranny, Andy, White, Neil M.

    Published 2015
    “…The results from experiments with screen-printed a piezoelectric sensor, mounted on an artificial finger-tip and including a cosmetic covering, are shown to detect surface information from regular texture patterns. For the automatic control of an artificial hand and to feedback information to the amputee, an algorithm has been developed based on the standard deviation of signal data from the sensor. …”
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  9. 9
    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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  10. 10
    Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction

    Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction by Abd Razak, Siti Safwana

    Published 2019
    “…Comparison of this framework continue in some of the state-of-the-arts algorithm in the literature and the results is outperformed based on the proposed algorithm experimental result.…”
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  11. 11
    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method

    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

    Published 2017
    “…The experimental results reveal that the developed algorithm is able to achieve an accuracy of 87.82% F1-measure based on images from the ECU database. …”
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  12. 12
    The Development of Color Based Visual Search Utility

    The Development of Color Based Visual Search Utility by Mohamed, Al Mabruk S.

    Published 2001
    “…As a result, several content- based image searching systems or met hods were developed. …”
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  13. 13
    Wood texture detection with conjugate gradient neural network algorithm

    Wood texture detection with conjugate gradient neural network algorithm by Widyarto, Setyawan, Suryasa, I. Nyoman, Khairul Annuar, Abdullah, Fajarianto, Otto, Mohd Shafry, Mohd Rahim, Priyandoko, Gigih, Budaya, Gilang Anggit

    Published 2017
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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, Nur Farahim

    Published 2014
    “…A working classification algorithm is developed by using MATLAB and the Fuzzy Logic Toolbox to differentiate and classify the staining pattern of HEp-2 cell images. …”
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  15. 15
    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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  16. 16
    Fruit recognition system / Nurul Husna Mohd Hofni

    Fruit recognition system / Nurul Husna Mohd Hofni by Nurul Husna, Mohd Hofni

    Published 2011
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  17. 17
    Obstacle detection for Unmanned Aerial Vehicle (UAV)

    Obstacle detection for Unmanned Aerial Vehicle (UAV) by Abdul Khaliq, Nor Aizatul Nabila, Ramli, Muhammad Faiz

    Published 2022
    “…Due to physical size restrictions and payload capacity, the lightweight Pi Camera and TF Luna LiDAR sensor were selected as the most suitable sensors for integration. In algorithm development and filtration is used to improve the accuracy of the feature matching process, which is required for classifying the obstacle region and free region of any texture obstacle. …”
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  18. 18
    A Steganalysis Classification Algorithm Based on Distinctive Texture Features

    A Steganalysis Classification Algorithm Based on Distinctive Texture Features by Hammad B.T., Ahmed I.T., Jamil N.

    Published 2023
    “…Therefore, in this research, we present a steganalysis classification method based on one of the texture features chosen, such as segmentation-based fractal texture analysis (SFTA), local binary pattern (LBP), and gray-level co-occurrence matrix (GLCM). …”
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  19. 19
    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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  20. 20
    Computer vision automation system for sorting partially overlapping tiles

    Computer vision automation system for sorting partially overlapping tiles by Hussin, Neam Tariq

    Published 2019
    “…A texture feature extraction algorithm based on (standard deviation of intensities and entropy) were developed and compared in the third component to identify overturned tiles from white tiles. …”
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