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5日前 -firstly proposed image super-resolution based on convolutional neural network (SRCNN) and achieved better image restoration [25] . Later, some researchers have ...

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

1日前 -... (SRCNN, FSRCNN, SRResNet, EDSR). Findings demonstrate superior performance across all SR methods, with Enhanced Deep Super-Resolution (EDSR) achieving the ...

6日前 -SRCNN [4] uses a large ImageNet dataset [3] as in its original paper [4] . For evaluation, two datasets are used: BSD200 [19] from the Berkeley Segmentation ...

4日前 -The pioneering work of SRCNN [27] marked the initiation of applying deep learning to SISR, employing a three-layer convolutional neural network for the task.

4日前 -Super Resolution Convolutional Neural Network (SRCNN) solves the problems of poor robustness and complex calculation of traditional image super-resolution ...

2日前 -The system counteracts the chromatic aberration while concurrently elevating the image resolution by introducing Gaussian filtering and image SRCNN based on ...

6日前 -[4] pioneered the adoption of deep learning for their. SRCNN model, which has since propelled CNN-based so- lutions outperforming traditional SR methods ...

6日前 -The pioneer in CNN-based algorithms was the super-resolution convolutional neural network (SRCNN) [8], and its enhancement has persisted to this day through ...