文件名称:Machine-learning

  • 所属分类:
  • matlab例程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2013-11-11
  • 文件大小:
  • 1.21mb
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  • 0次
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多帧图像超分辨率重建,通过机器学习来实现,效果不错。-Multi-fr a me image super-resolution reconstruction, through machine learning to achieve good results.
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下载文件列表





elleSR_0.2(Machine learning in multi-frame SR)\Average_Image.bmp

..............................................\elle_eval_huber.cpp

..............................................\elle_eval_huber.mexw32

..............................................\elle_eval_huber_grad.cpp

..............................................\elle_eval_huber_grad.mexw32

..............................................\getAvim.cpp

..............................................\getAvim.mexw32

..............................................\Ground_Truth_Image.bmp

..............................................\Huber_Image.bmp

..............................................\lena.png

..............................................\low-res 1.bmp

..............................................\low-res 2.bmp

..............................................\low-res 3.bmp

..............................................\low-res 4.bmp

..............................................\low-res 5.bmp

..............................................\makeLR.cpp

..............................................\makeLR.mexw32

..............................................\makeW.cpp

..............................................\makeW.mexw32

..............................................\mex_amub.cpp

..............................................\mex_amub.mexw32

..............................................\ML_Image.bmp

..............................................\netlab3_3\conffig.m

..............................................\.........\confmat.m

..............................................\.........\conjgrad.m

..............................................\.........\consist.m

..............................................\.........\Contents.m

..............................................\.........\convertoldnet.m

..............................................\.........\datread.m

..............................................\.........\datwrite.m

..............................................\.........\dem2ddat.m

..............................................\.........\demard.m

..............................................\.........\demev1.m

..............................................\.........\demev2.m

..............................................\.........\demev3.m

..............................................\.........\demgauss.m

..............................................\.........\demglm1.m

..............................................\.........\demglm2.m

..............................................\.........\demgmm1.m

..............................................\.........\demgmm2.m

..............................................\.........\demgmm3.m

..............................................\.........\demgmm4.m

..............................................\.........\demgmm5.m

..............................................\.........\demgp.m

..............................................\.........\demgpard.m

..............................................\.........\demgpot.m

..............................................\.........\demgtm1.m

..............................................\.........\demgtm2.m

..............................................\.........\demhint.m

..............................................\.........\demhmc1.m

..............................................\.........\demhmc2.m

..............................................\.........\demhmc3.m

..............................................\.........\demkmn1.m

..............................................\.........\demknn1.m

..............................................\.........\demmdn1.m

..............................................\.........\demmet1.m

..............................................\.........\demmlp1.m

..............................................\.........\demmlp2.m

..............................................\.........\demnlab.m

..............................................\.........\demns1.m

..............................................\.........\demolgd1.m

..............................................\.........\demopt1.m

.......................

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