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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    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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  10. 10
    Priority and dynamic quantum time algorithms for central processing unit scheduling

    Priority and dynamic quantum time algorithms for central processing unit scheduling by Mohammed, Maysoon A.

    Published 2018
    “…Central Processing Unit is scheduled using different types of scheduling algorithms. One of the most widely algorithm used in scheduling with sharing and batch operating systems is Round Robin. …”
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  11. 11
    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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  12. 12
    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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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    A Model for Evaluation of Cryptography Algorithm on UUM Portal

    A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

    Published 2004
    “…The simulation model was developed using Active Server Page, JavaScript and SQL 7.0 as database. …”
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  17. 17
    Prevention And Detection Mechanism For Security In Passive Rfid System

    Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

    Published 2013
    “…In addition, the randomness of the session key generated from the MLCG is verified using NIST test suite. Besides that, the security of the proposed protocol is validated using the formal analysis tool, AVISPA. …”
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  18. 18
    Herb recognition for mobile apps / Jumriyanie Baba

    Herb recognition for mobile apps / Jumriyanie Baba by Baba, Jumriyanie

    Published 2017
    “…An image of the leaf is captured and texture feature is extracted. Texture feature is preferable because color and shape features can be influenced by lighting. …”
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  19. 19
    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment

    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment by Aqel, Mohammad O. A.

    Published 2016
    “…Therefore, a new technique and algorithm were developed to resolve the image scale uncertainty. …”
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  20. 20
    Object texture recognition based on grasping force data using feedforward neural network / A. B. Roslan and R. L. A. Shauri

    Object texture recognition based on grasping force data using feedforward neural network / A. B. Roslan and R. L. A. Shauri by Roslan, A.B., Shauri, R.L.A.

    Published 2022
    “…A study on a three-fingered robot hand with a 6-axis force/torque sensor and position-based impedance control was developed to execute texture recognition during grasping tasks. …”
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