Novel cascaded CNN framework is designed for the multi-scale image SR task with a single trained model. •. Multi-scale feature mapping is proposed to extract ...
To implement the multi-scale image SR task with a single trained model and to further improve the performance of image SR, we propose a novel cascaded CNN ...
Aug 24, 2020 · In this paper, we propose a cascaded convolution neural network for image super-resolution (CSRCNN), which includes three cascaded Fast SRCNNs and each Fast ...
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Cascaded Convolutional Neural Network for Image Super-Resolution
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Nov 21, 2024 · Accurate Image Super-Resolution Using Very Deep Convolutional Networks ... We propose a new framework for estimating generative models via an ...
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of ...
Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented as a deep convolutional neural network (CNN) ...
Image super-resolution via a novel cascaded convolutional neural network framework. Signal Processing Image Communication Pub Date : 2018-02-03. DOI : 10.1016 ...
In this paper, we propose a new model called deep network cascade (DNC) to gradually upscale low-resolution images layer by layer, each layer with a small ...
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Experiments on image super-resolution demonstrate that the proposed DNC can gradually upscale a low-resolution image with the increase of network layers and ...
Novel cascaded CNN framework is designed for the multi-scale image SR task with a single trained model. • Multi-scale feature mapping is proposed to extract the ...