matlab插值代码解释-FSRCNN:由Pytorch和Matlab复制论文《加速超分辨率卷积神经网络》(CVPR2016)

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matlab插值代码解释FSRCNN 由Pytorch和Matlab复制《加速超分辨率卷积神经网络》(CVPR 2016)论文。 依存关系 Matlab 2016 火炬1.0.0 解释 论文作者url:提供的一些Matlab代码。 使用两种语言进行项目的主要原因是因为双三次插值的实现方式不同,这导致使用PSNR标准时结果的差异更大。 概述 网络概述和与SRCNN的比较: 用法 使用./data_pro/data_aug.m进行扩充。 使用./data_pro/generate_train.m生成train.h5。 使用./data_pro/generate_test.m生成test.h5。 乘坐train.py火车: python train.py 将Pytorch模型.pkl转换为Matlab矩阵.mat。 (weights.pkl-> weights.mat) python convert.py 使用./test/demo_FSRCNN.m获得结果。 结果 使用./model/weights.mat可以得到结果: Set5平均:重建PSNR = 32.52dB VS双三次PSNR

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