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  1. 1
    Note on the numerical solutions of the general matrix convolution equations by using the iterative methods and box convolution product

    Note on the numerical solutions of the general matrix convolution equations by using the iterative methods and box convolution product by Kilicman, Adem, Al-Zhour, Zeyad

    Published 2010
    “…We define the so-called box convolution product and study their properties in order to present the approximate solutions for the general coupled matrix convolution equations by using iterative methods. …”
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  2. 2
    On the connection between Kronecker and Hadamard convolution products of matrices and some applications.

    On the connection between Kronecker and Hadamard convolution products of matrices and some applications. by Kilicman, Adem, Al Zhour, Zeyad

    Published 2009
    “…Further we establish some attractive inequalities for Hadamard convolution product. It is also proved that the results can be extended to the finite number of matrices, and some basic properties of matrix convolution products are also derived.…”
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  3. 3
    Review of deep convolution neural network in image classification

    Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

    Published 2017
    “…This paper first introduces the rise and development of deep learning and convolution neural network, and summarizes the basic model structure, convolution feature extraction and pooling operation of convolution neural network. …”
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  4. 4
    Performance study on effect of convolutional coding in WCDMA system with AWGN and multipath rayleigh fading channel / Siti Noorafiza Sudin

    Performance study on effect of convolutional coding in WCDMA system with AWGN and multipath rayleigh fading channel / Siti Noorafiza Sudin by Sudin, Siti Noorafiza

    Published 2010
    “…This Thesis highlights the performance of Convolutional coding in WCDMA with different channel. …”
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  5. 5
    Enhanced Semantic Image Segmentation Through Convolutional and Atrous Convolution Techniques

    Enhanced Semantic Image Segmentation Through Convolutional and Atrous Convolution Techniques by Meghana, H.V., Ushashree, R.

    Published 2024
    “…This paper presents an enhanced method for semantic partitioning through merging traditional convolutional level and atrous (extended) convolution techniques. …”
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  6. 6
    Performance study on effect of convolutional coding in WCDMA system with AWGN and multipath rayleigh fading channel: article / Siti Noorafiza Sudin

    Performance study on effect of convolutional coding in WCDMA system with AWGN and multipath rayleigh fading channel: article / Siti Noorafiza Sudin by Sudin, Siti Noorafiza

    Published 2010
    “…This Thesis highlights the performance of Convolutional coding in WCDMA with different channel. …”
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  7. 7
    A review of Convolutional Neural Networks in Remote Sensing Image

    A review of Convolutional Neural Networks in Remote Sensing Image by Liu, Xinni, Han, Fengrong, Kamarul Hawari, Ghazali, Izzeldin, I. Mohd, Zhao, Yue

    Published 2019
    “…In this article, firstly we have summarized the basic structure and several classical convolutional neural network architectures. Secondly, the recent research problems on convolutional neural network are discussed. …”
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  8. 8
    Speech emotion recognition using convolution neural networks and deep stride convolutional neural networks

    Speech emotion recognition using convolution neural networks and deep stride convolutional neural networks by Wani, Taiba, Gunawan, Teddy Surya, Ahmad Qadri, Syed Asif, Mansor, Hasmah, Kartiwi, Mira, Ismail, Nanang

    Published 2020
    “…In this paper, we have modified a recently developed different network architecture of convolutional neural networks, i.e., Deep Stride Convolutional Neural Networks (DSCNN), by taking a smaller number of convolutional layers to increase the computational speed while still maintaining accuracy. …”
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  9. 9
    Convolutional neural network model in machine learning methods and computer vision for image recognition: a review

    Convolutional neural network model in machine learning methods and computer vision for image recognition: a review by R. M. Q. R., Jaapar, Muhamad Arifpin, Mansor

    Published 2018
    “…There are a number of reasons that convolutional neural networks (CNNs) are becoming important. …”
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  10. 10
    Developed convolutional encoder and viterbi decoder using C++

    Developed convolutional encoder and viterbi decoder using C++ by Chin Toong Hing

    Published 2023
    “…A Convolutional encoder (CE) and Viterbi algorithm (VA) is developed using c++ program to demonstrate the encoding and encoding for a 1/2 rate Convolutional encoder. …”
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  11. 11
    Performance Evaluation Of Convolutions And Atrous Convolutions In Deep Networks For Retinal Disease Segmentation On Optical Coherence Tomography Volumes

    Performance Evaluation Of Convolutions And Atrous Convolutions In Deep Networks For Retinal Disease Segmentation On Optical Coherence Tomography Volumes by Alsaih, Khaled, Yusoff, Mohd Z, Tang, Tong B, Faye, Ibrahima, Mériaudeau, Fabrice

    Published 2020
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  12. 12
    On finite product Of convolutions and classifications of hyperbolic and elliptic equations.

    On finite product Of convolutions and classifications of hyperbolic and elliptic equations. by Kilicman, Adem, Eltayeb, H.

    Published 2011
    “…It is shown that the classifications of hyperbolic and elliptic new equations are similar to the original equations that is the classification is invariant after finite double convolutions product.…”
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  13. 13
    A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks

    A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks by , Abdul Wahid, Khan, Adnan Umar, , Mukhtarullah, Khan, Sheroz, Shah, Jawad

    Published 2019
    “…Convolutional Sparse Coding (CSC) framework has been proposed recently to explain relation between Convolutional Neural Networks (CNNs) and sparse coding theory. …”
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  14. 14
    Convolution, coefficient and radius problems of certain univalent functions [QA331. M231 2009 f rb].

    Convolution, coefficient and radius problems of certain univalent functions [QA331. M231 2009 f rb]. by Haji Mohd, Maisarah

    Published 2009
    “…By making use of the properties of convolution and theory of subordination, several subclasses of meromorphic functions are introduced. …”
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  15. 15
    Character recognition of Malaysian vehicle license plate with deep convolutional neural networks

    Character recognition of Malaysian vehicle license plate with deep convolutional neural networks by How D.N.T., Sahari K.S.M.

    Published 2023
    “…Classification (of information); Computer networks; Convolution; Intelligent control; Intelligent robots; License plates (automobile); Neural networks; Optical character recognition; Robotics; Smart sensors; Background image; Convolutional networks; Data augmentation; Deep convolutional neural networks; Learning models; Vehicle license; Vehicle license plate recognition; Vehicle license plates; Deep neural networks…”
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  16. 16
    Convolution coder software implementation using VIiterbiDecoding algorithm

    Convolution coder software implementation using VIiterbiDecoding algorithm by Khalifa, Othman Omran, Al-Maznaee, Tariq, Munjid, Mahmood, Hussan, Aisha

    Published 2008
    “…This In this paper, Convolutional coder software implementation using Viterbi decoding algorithm for bitstream that has been encoded using Forward error correction is presented. …”
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  17. 17
    On finite products of convolutions and classifications of hyperbolic and elliptic equations.

    On finite products of convolutions and classifications of hyperbolic and elliptic equations. by Kilicman, Adem, Eltayeb, Hassan

    Published 2011
    “…It is shown that the classifications of hyperbolic and elliptic new equations are similar to the original equations that is the classification is invariant after finite double convolutions product.…”
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  18. 18
    The use of convolutional code for narrowband interference suppression in OFDM-DVBT system

    The use of convolutional code for narrowband interference suppression in OFDM-DVBT system by Abdullah, Aizura, Jamil, Muhammad Sobrun, Abdullah, Khaizuran, Ismail, Ahmad Fadzil

    Published 2015
    “…It is assumed that a spectrum of IMT-A system between 790-862 MHz interfere the spectrum of the OFDM signal in DVB-T band. Two types of convolutional code (CC) which are non-systematic convolutional code (NSCC) and recursive systematic convolutional code (RSCC) are proposed to mitigate NBI. …”
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  19. 19
    The use of convolutional code for narrowband interference suppression in OFDM-DVBT System

    The use of convolutional code for narrowband interference suppression in OFDM-DVBT System by Abdullah, Aizura, Jamal, Muhammad Sobrun Jamil, Abdullah, Khaizuran, Ismail, Ahmad Fadzil, Asnawi, Ani Liza

    Published 2014
    “…It is assumed that a spectrum of IMT-A system between 790-862 MHz interfere the spectrum of the OFDM signal in DVB-T band. Two types of convolutional code (CC) which are non-systematic convolutional code (NSCC) and recursive systematic convolutional code (RSCC) are proposed to mitigate NBI. …”
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  20. 20
    Necessery and Sufficient Condition for Extention of Convolution Semigroup

    Necessery and Sufficient Condition for Extention of Convolution Semigroup by Mohd Jaffar, Mai Zurwatul Ahlam

    Published 2007
    Subjects: “…Convolutions (Mathematics).…”
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