Search Results - (( model visualization a algorithm ) OR ( time estimation based algorithm ))*

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  1. 1

    Denosing of natural image based on non-linear threshold filtering using discrete wavelet transformation by Khmag, Asem, Ramli, Abdul Rahman, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari

    Published 2014
    “…In this study the result shows that the proposed denoising algorithm based on semi-soft threshold algorithm outperforms the traditional wavelet denoising techniques in terms of visual quality and subjective scales, where it preserved the edges, ridges details of the reconstructed image and the quality of visualization shape as well. …”
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    Article
  2. 2

    Denoising of digital images using second generation wavelet transforms-hidden markov model by Khmag, Asem Ib Mohamed

    Published 2016
    “…In this issue, a newly developed algorithm based on second-generation wavelet transformation using semi-soft thresholding is introduced. …”
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    Thesis
  3. 3

    EEG-based brain source localization using visual stimuli by Jatoi, M.A., Kamel, N., Malik, A.S., Faye, I., Bornot, J.M., Begum, T.

    Published 2016
    “…These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. …”
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    Article
  4. 4
  5. 5

    Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins by Sidek L.M., Basri H., Marufuzzaman M., Deros A.M., Osman S., Hassan F.A.

    Published 2024
    “…So, in this research, a real-time flood inundation map (FIM) is used to develop the ML-based visualization (ML_V) method to characterize the collected dataset. …”
    Book chapter
  6. 6

    Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

    Published 2006
    “…A gain-based correction method; probability density function model are used to cluster white and gray matters, cerebrospinal fluid, and meninges. …”
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    Thesis
  7. 7

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…Learning a model in a virtual environment might potentially fail to generalize to the actual world. …”
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    Monograph
  8. 8

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…Based on the final denoised images, the model has proven its reliability, in terms of both visual quality and quantitative evaluation. …”
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    Thesis
  9. 9

    Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System by Al_Fugara, A’kif Mohammed Salem

    Published 2008
    “…A physical based, distributed hydrological model was developed to route overland flows during isolated HISD storms. …”
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    Thesis
  10. 10

    Evaluation of cracks and disintegrations using close-range digital photogrammetry and image processing technique by Ling, Tung Chai

    Published 2005
    “…The algorithms developed in this study are capable of identifying type of cracking and its severity level at the accuracy about 90%. …”
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    Thesis
  11. 11

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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    Thesis
  12. 12

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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    Book Chapter
  13. 13

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…This thesis describes the development of an efficient algorithm for solving nonlinear stochastic optimal control problems in discrete-time based on the principle of model-reality differences. …”
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    Thesis
  14. 14

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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    Thesis
  15. 15

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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    Thesis
  16. 16

    Time Difference Of Arrival Estimation Using Fast Fourier Transform Overlap For Underwater Positioning by Tan, Chee Sheng

    Published 2019
    “…This project presents an underwater acoustic positioning system based on time difference of arrival (TDOA) measurement. …”
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    Thesis
  17. 17

    Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system by Abdolee, Reza

    Published 2006
    “…Firstly it has investigated the performance of MIMO-STBC system and surveyed the effect of imperfect channel estimation on performance of MIMO-OFDM system. Secondly, it has focused on training based channel estimation algorithm for MIMO-OFDM system. …”
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    Thesis
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  19. 19

    Computed tomography and echocardiography image fusion technique for cardiac images by Kalahroodi, Samaneh Mazaheri

    Published 2016
    “…It is a new geometrically level Set algorithm for the segmentation of the endocardial contours in echocardiographic images in presence of intensity non-uniformity. …”
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    Thesis
  20. 20

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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    UMK Etheses