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    • Architecture of the superresolution convolutional neural network...

    1. https://www.researchgate.net
    2. figure
    3. Architecture-of-th...

    2024/4/15 -In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for ...


    FFmpeg Filters Documentation

    1. https://ffmpeg.org
    2. ffmpeg-filters

    56分前 -1 Description. This document describes filters, sources, and sinks provided by the libavfilter library. 2 Filtering Introduction.


    Given a low-resolution image Y, the first convolutional layer of the...

    1. https://www.researchgate.net
    2. figure
    3. Given-a-low-resol...

    2024/5/2 -Their model, known as SRCNN, aimed to learn a mapping function directly from low-resolution to highresolution images. ... ... The quantitative results were ...


    Enhancing Video Quality with Super-Resolution

    1. https://streaminglearningcenter.com
    2. Articles
    1. https://streaminglearningcenter.com
    2. Articles

    2024/4/23 -SRCNN (Super-Resolution Convolutional Neural Network): This filter implements the SRCNN ... The SRCNN filter can upscale video by factors of 2, 3, or 4. ESPCN ...


    Set14 - 4x upscaling Benchmark (Image Super-Resolution)

    1. https://paperswithcode.com
    2. sota
    1. https://paperswithcode.com
    2. sota

    2024/5/4 -×. Image Super-Resolution on Set14 - 4x upscaling. Leaderboard; Dataset. View. PSNR, SSIM, MOS. by. Date, SSIM, MOS. Created with Highcharts 9.3.0 PSNR SRCNN ​ ...


    The Problem Of Image Super-Resolution, Denoising And ...

    PDF
    1. https://arxiv.org
    2. pdf
    PDF
    1. https://arxiv.org
    2. pdf

    2024/4/16 -Abstract— In this article, we address the challenges of image super-resolution and noise reduction, which are crucial for enhancing the quality.


    Multi-level feature interaction image super-resolution network based on ...

    1. https://www.sciencedirect.com
    2. science
    3. article
    4. pii

    6日前 -Since the proposal of SRCNN model by Dong et al. (2014) in the field of super-resolution, the SISR methods based on convolutional neural networks have been ...


    Uncertainty-driven mixture convolution and transformer network for remote ...

    1. https://www.nature.com
    2. scientific reports
    3. articles

    2024/4/24 -Dong et al. introduced the seminal SISR approach based on very simple but effective CNNs known as SRCNN. Despite comprising only three convolutional layers, ...


    A blind image super-resolution network guided by kernel ... - NCBI

    1. https://www.ncbi.nlm.nih.gov
    2. articles
    3. PMC11045763

    2024/4/26 -SR of bicubic and multiple degradation. The pioneering work of SRCNN has successfully motivated interest among researchers in the field of SR. Inspired by ...


    PyTorch Hub

    1. https://pytorch.org
    2. hub
    1. https://pytorch.org
    2. hub

    2日前 -PyTorch. Hub. Discover and publish models to a pre-trained model repository designed for research exploration. Check out the models for Researchers, ...

    All Research Models (52)-Torch.hub-3D ResNet-HybridNets