超分辨卷积神经网络 Training-code-for-SRCNN

代码说明：

  超分辨卷积神经网络，深度学习，MATLAB代码，获取深度学习的训练数据(Super-resolution convolution neural network, the depth of learning, MATLAB code, get deep learning of the training data)

文件列表：

SRCNN
.....\generate_test.m,1771,2015-07-08
.....\generate_train.m,1769,2015-07-08
.....\modcrop.m,279,2015-03-17
.....\Readme.txt,1088,2015-07-01
.....\saveFilters.m,1318,2015-07-01
.....\SRCNN_mat.prototxt,1478,2015-07-01
.....\SRCNN_net.prototxt,1705,2015-07-01
.....\SRCNN_solver.prototxt,566,2015-07-01
.....\store2hdf5.m,2897,2015-06-05
.....\Test
.....\....\Set14





.....\....\.....\face.bmp,228584,2015-03-17
.....\....\.....\flowers.bmp,543054,2015-03-17
.....\....\.....\foreman.bmp,304182,2015-03-17
.....\....\.....\lenna.bmp,786486,2015-03-17
.....\....\.....\man.bmp,786486,2015-03-17
.....\....\.....\monarch.bmp,1179702,2015-03-17
.....\....\.....\pepper.bmp,786486,2015-03-17
.....\....\.....\ppt3.bmp,1041782,2015-03-17
.....\....\.....\zebra.bmp,688214,2015-03-17
.....\....\Set5





.....\test.txt,23,2015-07-01
.....\Train





.....\.....\t14.bmp,76990,2015-03-17
.....\.....\t15.bmp,126618,2015-03-17
.....\.....\t16.bmp,83894,2015-03-17
.....\.....\t17.bmp,69786,2015-03-17
.....\.....\t18.bmp,55782,2015-03-17
.....\.....\t19.bmp,96174,2015-03-17
.....\.....\t2.bmp,92418,2015-03-17
.....\.....\t20.bmp,18462,2015-03-17
.....\.....\t21.bmp,41346,2015-03-17
.....\.....\t22.bmp,59718,2015-03-17
.....\.....\t23.bmp,46902,2015-03-17
.....\.....\t24.bmp,37290,2015-03-17
.....\.....\t25.bmp,125190,2015-03-17
.....\.....\t26.bmp,58742,2015-03-17
.....\.....\t27.bmp,126030,2015-03-17
.....\.....\t28.bmp,92550,2015-03-17
.....\.....\t29.bmp,87526,2015-03-17
.....\.....\t3.bmp,89334,2015-03-17
.....\.....\t30.bmp,61662,2015-03-17
.....\.....\t31.bmp,101670,2015-03-17
.....\.....\t32.bmp,86646,2015-03-17
.....\.....\t33.bmp,81706,2015-03-17
.....\.....\t34.bmp,66362,2015-03-17
.....\.....\t35.bmp,125306,2015-03-17
.....\.....\t36.bmp,114102,2015-03-17
.....\.....\t37.bmp,312390,2015-03-17
.....\.....\t38.bmp,200054,2015-03-17
.....\.....\t39.bmp,197350,2015-03-17
.....\.....\t4.bmp,128646,2015-03-17
.....\.....\t40.bmp,200082,2015-03-17
.....\.....\t42.bmp,202814,2015-03-17
.....\.....\t43.bmp,157134,2015-03-17
.....\.....\t44.bmp,115722,2015-03-17
.....\.....\t45.bmp,120114,2015-03-17
.....\.....\t46.bmp,355146,2015-03-17
.....\.....\t47.bmp,143574,2015-03-17
.....\.....\t48.bmp,135462,2015-03-17
.....\.....\t49.bmp,243022,2015-03-17
.....\.....\t5.bmp,70734,2015-03-17
.....\.....\t50.bmp,259958,2015-03-17
.....\.....\t51.bmp,251910,2015-03-17
.....\.....\t52.bmp,207090,2015-03-17
.....\.....\t53.bmp,237166,2015-03-17
.....\.....\t54.bmp,153234,2015-03-17
.....\.....\t55.bmp,173502,2015-03-17
.....\.....\t56.bmp,98694,2015-03-17
.....\.....\t57.bmp,112078,2015-03-17
.....\.....\t58.bmp,133374,2015-03-17
.....\.....\t59.bmp,214134,2015-03-17
.....\.....\t6.bmp,90102,2015-03-17
.....\.....\t60.bmp,141394,2015-03-17
.....\.....\t61.bmp,111254,2015-03-17
.....\.....\t62.bmp,118194,2015-03-17
.....\.....\t63.bmp,148726,2015-03-17
.....\.....\t64.bmp,117534,2015-03-17
.....\.....\t65.bmp,114102,2015-03-17
.....\.....\t66.bmp,234090,2015-03-17
.....\.....\t7.bmp,83898,2015-03-17
.....\.....\t8.bmp,102654,2015-03-17
.....\.....\t9.bmp,37854,2015-03-17
.....\.....\tt1.bmp,407454,2015-03-17