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  1. 1

    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
    “…Plots for the output from the algorithm show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. …”
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  2. 2

    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 output from the algorithm is the frequency spectrum of a signal. Plots, from the output of the algorithm, show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. …”
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  3. 3

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

    Published 2019
    “…Finally, this thesis present Outlier Detection, window size of 5 for Median Filter and fill-in invalid disparity to utilize the last stage of SMA to handle the accuracy of disparity map in regions of occluded, repetitive and low texture. …”
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  4. 4
  5. 5

    Disparity Refinement Based on Depth Image Layers Separation for Stereo Matching Algorithms by Abd Manap, Nurulfajar, Soraghan, John J.

    Published 2012
    “…The similarity metric finds the pixel points between the left and right under the fixed window (FW) searching process. With this approach, the raw disparity depth map obtained is not smooth and contained errors particularly with the depth discontinuities and unable to detect the uniform areas and repetitive patterns. …”
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  6. 6

    Segmentation of Malay syllables in connected digit speech using statistical approach by Salam, M.S., Mohamad, Dzulkifli, Saleh, S.H.

    Published 2008
    “…Experiments were conducted to see the effect of number of the auto regressive model order p and sliding window length L in Brandt’s algorithm and Divergence algorithm in giving better match of the segmentation points. …”
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  7. 7
  8. 8

    Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni by Farahiyah , Jasni

    Published 2018
    “…The finalized configuration that resulted in the best response was adopted and used to collect data for training and classifying the gait phase using pattern recognition method. The performance of the proposed sensory system was evaluated by checking the accuracy of the pattern recognition algorithm in detecting the gait phases at different speeds of normal walking. …”
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    Thesis
  9. 9

    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

    Published 2014
    “…This gives a more practical functionality for such a system to be used in a wearable fashion over the existing Electroencephalogram (EEG) based seizure detection systems due to their complex pattern classification methodologies. …”
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  10. 10

    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This gives a more practical functionality for such a system to be used in a wearable fashion over the existing Electroencephalogram (EEG) based seizure detection systems due to their complex pattern classification methodologies. …”
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  11. 11

    A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment by Tan, Ming Gui, Ho, Jee Hou, Goh, Hui Ting, Ng, Hoon Kiat, Abdul Latif, Lydia, Mazlan, Mazlina

    Published 2019
    “…To achieve these objectives, 30 stroke survivors with different levels of gait impairments were recruited to perform TUG. sEMG signals from Tibialis Anterior (TA) and Gastrocnemius Lateral (GL) were acquired in a 5-meter walk test. Sliding window Higuchi fractal dimension algorithm was applied to sEMG of these TA and GL muscles to determine the fractal properties. …”
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