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2024/1/9 -The Super-Resolution Convolutional Neural Network (SRCNN) is a pioneering deep learning approach specifically designed for image super-resolution. Super- ...

2024/2/22 -At its core, SRCNN is a type of deep neural network designed specifically for image super-resolution. Unlike traditional methods that rely on interpolation ...

2024/1/6 -They utilized a three-layer convolutional neural network to understand the mapping between low-resolution and high-resolution images. An overview of the SRCNN ...

2024/3/3 -Where SRCNN stands for the SRCNN 9-5-5 ImageNet model [7] , TNRD stands for the Trainable Nonlinear Reaction Diffusion Model from [3] and ESPCN stands for ...

2023/12/15 -This study compares four different super-resolution techniques, including super-resolution convolutional neural network (SRCNN), efficient sub-pixel ...

2023/12/8 -Super Resolution with SRCNN. SRCNN is a deep convolutional neural network that learns end-to-end mapping of low resolution to high resolution images.

2024/3/17 -The formulation of SRCNN is relatively simple and can be envisioned as an ordinary CNN that approximates the complex mapping between the LR and HR spaces in an ...

2024/2/18 -In the paper, we propose a two-stage SR method for compressed images, which consists of the Compression Artifact Removal Module (CARM) and Super-Resolution ...

2024/4/2 -Wavelet embedding super-resolution convolution neural network(W-SRCNN) architecture, including training pipelines. ... Image evaluation. We evaluated performance ...