Search Results - multi-layered convolutional sparse coding

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  1. 1

    Analysis of Top-Down Connections in Multi-Layered Convolutional Sparse Coding by Edlund, Joakim, Guillemot, Christine, Sjostrom, Marten

    ISSN: 2473-3628
    Published: IEEE 06.10.2021
    “… Multi-Layered Convolutional Sparse Coding (ML-CSC) based on a cascade of convolutional layers in which each layer can be approximately explained by the following layer can be seen as a biologically inspired framework…”
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    Conference Proceeding
  2. 2

    Multi-Layer Basis Pursuit for Compressed Sensing MR Image Reconstruction by Wahid, Abdul, Shah, Jawad Ali, Khan, Adnan Umar, Ahmed, Manzoor, Razali, Hanif

    ISSN: 2169-3536, 2169-3536
    Published: Piscataway IEEE 2020
    Published in IEEE access (2020)
    “… Inspired from recent research works on multi-layer convolutional sparse coding (ML-CSC) theory to model deep neural networks, this work proposes a multi-layer basis…”
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    Journal Article
  3. 3

    Multi-Layered Basis Pursuit Algorithms for Classification of MR Images of Knee ACL Tear by Wahid, Abdul, Shah, Jawad Ali, Khan, Adnan Umar, Ullah, Mukhtar, Ayob, Mohd Zaki

    ISSN: 2169-3536, 2169-3536
    Published: Piscataway IEEE 2020
    Published in IEEE access (2020)
    “…Deep learning architectures have been extensively used in recent years for the classification of biomedical images to assist clinicians for diagnosis and…”
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    Journal Article
  4. 4

    Multi Attention Convolutional Sparse Coding U-Net for Enhanced Land-Use and Land-Cover Segmentation Using Hyperspectral Images by Yele, Vijaykumar P., Badhe, Namdeo Baban, Alegavi, Sujata, Sedamkar, R. R.

    ISSN: 1557-2072, 1557-2064, 1557-2072
    Published: New York Springer US 01.12.2025
    Published in Sensing and imaging (01.12.2025)
    “… with the architectural complexities hindering the performance across different datasets and tasks. In response to this, a Multi Attention Convolutional sparse coding U-network Feed-forward Network (MACUFN…”
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    Journal Article
  5. 5

    Lamb wave-based damage assessment for composite laminates using a deep learning approach by Zhang, Han, Wang, Fan, Lin, Jing, Hua, Jiadong

    ISSN: 0041-624X, 1874-9968, 1874-9968
    Published: Netherlands Elsevier B.V 01.07.2024
    Published in Ultrasonics (01.07.2024)
    “…•A convolutional sparse coding-based UNet (CSCUNet) is proposed to analyze the ultrasonic Lamb wave signal, which enables high-resolution imaging of damage in composite laminates…”
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    Journal Article
  6. 6

    A Multilayered Convolutional Sparse Coding Framework for Modeling of Pooling Operation of Convolution Neural Networks by Wahid, Abdul, Umar Khan, Adnan, Mukhtarullah, Khan, Sheroz, Shah, Jawad

    ISSN: 2640-6535
    Published: IEEE 01.08.2019
    “…Convolutional Sparse Coding (CSC) framework has been proposed recently to explain relation between Convolutional Neural Networks (CNNs…”
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    Conference Proceeding
  7. 7

    Improved Image Generation via Sparse Modeling by Ganz, Roy, Elad, Michael

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 13.05.2022
    Published in arXiv.org (13.05.2022)
    “…The interest of the deep learning community in image synthesis has grown massively in recent years. Nowadays, deep generative methods, and especially…”
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    Paper
  8. 8

    Complex Valued and Layer Based Categorization of Synthetic Aperture Radar Patches by Sipos, Danijel, Gleich, Dusan, Planinsic, Peter

    Published: IEEE 20.10.2021
    “… In this paper a sparse coding approach is designed in multi layered architecture. This this paper proposes a layered based sparse coding using approaches introduced within…”
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    Conference Proceeding
  9. 9

    Multi-layer Convolutional Sparse Coding Framework for Restoration of Under-sampled MR Images by Wahid, Abdul, Ullah, Abdul Wahab Usman, Kadir, Kushairy, Saadain, Syed

    ISSN: 2642-2077
    Published: IEEE 17.05.2021
    “…Magnetic Resonance Imaging (MRI) plays an important role in the diagnosis of different pathologies associated with human anatomy. The need to acquire images…”
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    Conference Proceeding