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 ...
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2023/12/31 -[9] define an image r which represents the difference between image xi's real high- resolution image yi and predicted high-resolution image yi . Hence, the ...
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 ...
2024/3/15 -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 ...
2024/3/26 -Deep Learning, Image Super-Resolution, Quantitative Evaluation, SRCNN, Visual Quality Assessment. Abstract. This research digs into the space of Image Super ...
2024/2/23 -Land cover semantic segmentation in high-spatial resolution satellite images plays a vital role in efficient management of land resources, smart agriculture, ...
2023/12/15 -This study compares four different super-resolution techniques, including super-resolution convolutional neural network (SRCNN), efficient sub-pixel ...
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 ...