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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复制论文《加速超分辨率卷积神经网络》(CVPR2016)
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》(CVPR2016)论文。
依存关系Matlab2016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次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:pythontrain.py将Pytorch模型.pkl转换为Matlab矩阵.mat。
(weights.pkl->weights.mat)pythonconvert.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=32.52dBVS双三次PSNR 本软件ID:19101408

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