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 ...
2023/12/31 -Illustration of SRCNN and VDSR for image SR. (Image x i represents the input image which is down sampled and interpolated from high-resolution image y i ...
2024/3/15 -In this paper, we aim at accelerating the current SRCNN, and propose a compact hourglass-shape CNN structure for faster and better SR. We re-design the SRCNN ...
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 ...
2024/3/26 -Deep Learning, Image Super-Resolution, Quantitative Evaluation, SRCNN, Visual Quality Assessment. Abstract. This research digs into the space of Image Super ...
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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 ...
2023/12/15 -This study compares four different super-resolution techniques, including super-resolution convolutional neural network (SRCNN), efficient sub-pixel ...
2024/3/15 -The pioneering SR method is SRCNN proposed by Dong et al. [6, 7] . They establish the relationship between the traditional sparse-coding based SR methods and ...