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  1. 1
    Improved Switching-Basedmedian Filter For Impulse Noise Removal

    Improved Switching-Basedmedian Filter For Impulse Noise Removal by Teoh, Sin Hoong

    Published 2013
    “…This thesis proposed a new algorithm to reduce impulse noise from digital images. …”
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  2. 2
    Development of a new nonlinear filtering algorithm for impulse noise reduction

    Development of a new nonlinear filtering algorithm for impulse noise reduction by Ahmad, Mohd Ashraf

    Published 2020
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    Research Report
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  3. 3
    Noise Elimination for Image Subtraction in Printed Circuit Board Defect Detection Algorithm

    Noise Elimination for Image Subtraction in Printed Circuit Board Defect Detection Algorithm by Zuwairie, Ibrahim, Ismail, Ibrahim, Zulfakar, Aspar, Kamal, Khalil, Sophan Wahyudi, Nawawi, Muhammad Arif, Abdul Rahim, Wan Khairunizam, Wan Ahmad

    Published 2013
    “…Even though the image subtraction operation able to detect all defects occurred on PCB, some unwanted noise could be detected as well. …”
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  4. 4
    A Partitioning Method In Noise Reduction And A Hybrid Convex Hull Algorithm For Fingertips Detection On An Outstretched Hand.

    A Partitioning Method In Noise Reduction And A Hybrid Convex Hull Algorithm For Fingertips Detection On An Outstretched Hand. by Woun , Bo Shen

    Published 2016
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  5. 5
    A novel algorithm to detect a QPSK signal with the minimum number of samples

    A novel algorithm to detect a QPSK signal with the minimum number of samples by Mohammed, Saleh, Hilmi, Sanusi, Abubakar, Adamu, Haruna, Chiroma, Edi, Sutoyo, Mungad, Mu, Tutut, Herawan

    Published 2015
    “…The algorithm was simulated and tested using ANSI C++. …”
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  6. 6
    Removal of Low Level Random-Valued Impulse Noise Using Dual Sliding Statistics Switching Median Filter

    Removal of Low Level Random-Valued Impulse Noise Using Dual Sliding Statistics Switching Median Filter by Muhammad Salihin, Saealal, Mohd Helmi, Suid, Mohd Falfazli, Mat Jusof, Nor Ashidi, Mat Isa

    Published 2014
    “…The proposed DSSSM filter is made up of two subunits; i.e. impulse noise detection and noise filtering. Initially, the impulse noise detection stage of DSSSM algorithm begins by processing the statistics of a localized detection window in sorted order and non-sorted order, simultaneously. …”
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  7. 7
    Microcrack Detection And Noise Reduction In Integrated Circuit Packages

    Microcrack Detection And Noise Reduction In Integrated Circuit Packages by Koh, Ye Sheng

    Published 2018
    “…Three algorithms are tested and evaluated in terms of microcrack detection and noise reduction which are probability based thresholding, histogram equalization, and modified Perona-Malik’s anisotropic diffusion methods. …”
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  8. 8
    Dual Sliding Statistics Switching Median Filter for the Removal of Low Level Random-Valued Impulse Noise

    Dual Sliding Statistics Switching Median Filter for the Removal of Low Level Random-Valued Impulse Noise by Mohd Helmi, Suid, Mohd Falfazli, Mat Jusof, Mohd Ashraf, Ahmad

    Published 2018
    “…The proposed DSSSM filter is made up of two subunits; i.e. Impulse noise detection and noise filtering. Initially, the impulse noise detection stage of DSSSM algorithm begins by processing the statistics of a localized detection window in sorted order and non-sorted order, simultaneously. …”
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  9. 9
    A cascading fuzzy logic with image processing algorithm-based defect detection for automatic visual inspection of industrial cylindrical object’s surface

    A cascading fuzzy logic with image processing algorithm-based defect detection for automatic visual inspection of industrial cylindrical object’s surface by Ali, Mohammed A. H., Au, Kai Lun

    Published 2018
    “…The 1st stage of fuzzy logic algorithm is used to eliminate the low noise from the captured images; however, the 2nd stage is used to differentiate between the big noise and defects on the objects. …”
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  10. 10
    An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms

    An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms by Mohammed A. H., Ali, Muhammad, Baggash, Jaloliddin, Rustamov, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Najm Al-Deen N., Abdo, Mubarak H. G., Abdo, Talep S., Mohammed, Ameen A., Hasan, Ali N., Abdo, Sherzod, Turaev, Yusoff, Nukman

    Published 2023
    “…The purpose of this research is to detect the rust in oil tanks by localizing visual inspection technology using UAVs, as well as to develop algorithms to distinguish between defects and noise. …”
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  11. 11
    Quantitative analysis evaluation of image reconstruction algorithms between digital and analog PET-CT

    Quantitative analysis evaluation of image reconstruction algorithms between digital and analog PET-CT by Chen, Ew-Jun *, Haniff Shazwan, Safwan Selvam, Lee, Hee Siang, Chew, Ming Tsuey *

    Published 2023
    “…Ordered Subset Expectation Maximisation (OSEM) is a widely used statistical iterative reconstruction algorithm in PET-CT due to its dependability, reconstruction quality and adequate signal-to-noise ratio. …”
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  12. 12
    Detection of Gaussian noise and its level using deep convolutional neural network

    Detection of Gaussian noise and its level using deep convolutional neural network by Chuah, J.H., Khaw, H.Y., Soon, F.C., Chow, C.O.

    Published 2017
    “…Our experiments and results have proven that this model is capable of performing Gaussian noise detection and its noise level classification.…”
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  13. 13
    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying

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

    Published 2019
    “…The designed system is validated by using images treated with noise of single and combination of various types. …”
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  14. 14
    Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals

    Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals by Acharya, U.R., Fujita, H., Oh, S.L., Hagiwara, Y., Tan, J.H., Adam, M.

    Published 2017
    “…Therefore, we propose a novel approach to automatically detect the MI using ECG signals. In this study, we implemented a convolutional neural network (CNN) algorithm for the automated detection of a normal and MI ECG beats (with noise and without noise). …”
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  15. 15
    Signal quality measures for unsupervised blood pressure measurement

    Signal quality measures for unsupervised blood pressure measurement by Abdul Sukora, Jumadi, Redmond, S J, Chan, G S H, Lovell, N H

    Published 2012
    “…The time between an identified noise section and a verified Korotkoff pulse was the key feature used to determine the validity of possible systolic and diastolic pressures in noise contaminated Korotkoff sounds. …”
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  16. 16
    Detection of Gaussian noise and its level using deep convolutonal neural network

    Detection of Gaussian noise and its level using deep convolutonal neural network by Joon, H.C., Hui, Y.K., Foo, C.S., Chee, O.C.

    Published 2017
    “…Our experiments and results have proven that this model is capable of performing Gaussian noise detection and its noise level classification.…”
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  17. 17
    Software User Interface and Algorithm Development for Signal and Noise Characterization

    Software User Interface and Algorithm Development for Signal and Noise Characterization by Phoong, Wei Siang

    Published 2015
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  18. 18
    Real-time algorithmic music composition application.

    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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  19. 19
    Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm

    Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm by Khammar, Mohammad Reza, Saripan, M. Iqbal, Marhaban, Mohammad Hamiruce, Ishak, Asnor Juraiza

    Published 2014
    “…Detection is provided by using statistical analysis in each window, then the appropriate replacement for the noisy pixel is conducted from given values inside the current window or adjacent reconstructed pixels based on mean calculation and also, for very high density of noise which density of noise is bigger than 80%, the reconstruction is based on a recursive approach. …”
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  20. 20
    Application-Programming Interface (API) for Song Recognition Systems

    Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

    Published 2024
    “…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”
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