snrmatlab代码-FBPConvNet:用于计算机断层扫描的FBPConvNet

上传者: 38500709 | 上传时间: 2025-09-02 23:05:44 | 文件大小: 15.63MB | 文件类型: ZIP
snr matlab代码FBPConvNet-Matlab 深度卷积神经网络解决成像逆问题 自述文件 在启动FBPConvNet之前,必须正确安装MatConvNet()。 (对于GPU,它需要不同的编译。) 正确修改main.m和Evaluation.m文件中的matconvnet路径。 首先,下载2个链接; (1)预训练网络:,然后将此网络放入“ pretrain”文件夹中(2)数据集:只需将此数据与main.m放在同一文件夹中 使用main.m进行培训。 训练后,运行评估版.m以部署测试数据集。 *注意:仅提供幻像数据集(x20)。 SNR值可能与我们的论文略有不同。 *注意:这些代码主要在具有GPU TITAN X的Matlab 2016a上运行(体系结构:Maxwell) 联系人:Kyong Jin(), 特别感谢Junhong Min(三星电子的高级研究员)提供了初始代码。

文件下载

资源详情

[{"title":"( 434 个子文件 15.63MB ) snrmatlab代码-FBPConvNet:用于计算机断层扫描的FBPConvNet","children":[{"title":"references.bib <span style='color:#111;'> 4.53KB </span>","children":null,"spread":false},{"title":"COPYING <span style='color:#111;'> 735B </span>","children":null,"spread":false},{"title":"normalize_cpu.cpp <span style='color:#111;'> 12.35KB </span>","children":null,"spread":false},{"title":"roipooling_cpu.cpp <span style='color:#111;'> 12.17KB </span>","children":null,"spread":false},{"title":"pooling_cpu.cpp <span style='color:#111;'> 10.22KB </span>","children":null,"spread":false},{"title":"bnorm_cpu.cpp <span style='color:#111;'> 10.18KB </span>","children":null,"spread":false},{"title":"tinythread.cpp <span style='color:#111;'> 8.31KB </span>","children":null,"spread":false},{"title":"im2row_cpu.cpp <span style='color:#111;'> 7.98KB </span>","children":null,"spread":false},{"title":"imread_libjpeg.cpp <span style='color:#111;'> 6.35KB </span>","children":null,"spread":false},{"title":"bilinearsampler_cpu.cpp <span style='color:#111;'> 6.31KB </span>","children":null,"spread":false},{"title":"imread_gdiplus.cpp <span style='color:#111;'> 6.02KB </span>","children":null,"spread":false},{"title":"imread_quartz.cpp <span style='color:#111;'> 5.24KB </span>","children":null,"spread":false},{"title":"subsample_cpu.cpp <span style='color:#111;'> 2.75KB </span>","children":null,"spread":false},{"title":"imread.cpp <span style='color:#111;'> 1.44KB </span>","children":null,"spread":false},{"title":"nnbias.cpp <span style='color:#111;'> 1.25KB </span>","children":null,"spread":false},{"title":"copy_cpu.cpp <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"vl_nnbilinearsampler.cpp <span style='color:#111;'> 122B </span>","children":null,"spread":false},{"title":"nnfullyconnected.cpp <span style='color:#111;'> 121B </span>","children":null,"spread":false},{"title":"vl_nnnormalize.cpp <span style='color:#111;'> 116B </span>","children":null,"spread":false},{"title":"vl_imreadjpeg.cpp <span style='color:#111;'> 115B </span>","children":null,"spread":false},{"title":"vl_imreadjpeg_old.cpp <span style='color:#111;'> 115B </span>","children":null,"spread":false},{"title":"vl_nnroipool.cpp <span style='color:#111;'> 114B </span>","children":null,"spread":false},{"title":"vl_taccummex.cpp <span style='color:#111;'> 114B </span>","children":null,"spread":false},{"title":"vl_cudatool.cpp <span style='color:#111;'> 113B </span>","children":null,"spread":false},{"title":"nnbilinearsampler.cpp <span style='color:#111;'> 113B </span>","children":null,"spread":false},{"title":"nnroipooling.cpp <span style='color:#111;'> 113B </span>","children":null,"spread":false},{"title":"vl_nnconvt.cpp <span style='color:#111;'> 112B </span>","children":null,"spread":false},{"title":"nnsubsample.cpp <span style='color:#111;'> 112B </span>","children":null,"spread":false},{"title":"vl_nnbnorm.cpp <span style='color:#111;'> 112B </span>","children":null,"spread":false},{"title":"vl_nnconv.cpp <span style='color:#111;'> 111B </span>","children":null,"spread":false},{"title":"nnnormalize.cpp <span style='color:#111;'> 111B </span>","children":null,"spread":false},{"title":"vl_nnpool.cpp <span style='color:#111;'> 111B </span>","children":null,"spread":false},{"title":"vl_tmove.cpp <span style='color:#111;'> 110B </span>","children":null,"spread":false},{"title":"datamex.cpp <span style='color:#111;'> 109B </span>","children":null,"spread":false},{"title":"nnpooling.cpp <span style='color:#111;'> 107B </span>","children":null,"spread":false},{"title":"data.cpp <span style='color:#111;'> 106B </span>","children":null,"spread":false},{"title":"nnbnorm.cpp <span style='color:#111;'> 103B </span>","children":null,"spread":false},{"title":"nnconv.cpp <span style='color:#111;'> 101B </span>","children":null,"spread":false},{"title":"fixes.css <span style='color:#111;'> 2.89KB </span>","children":null,"spread":false},{"title":"base.css <span style='color:#111;'> 2.29KB </span>","children":null,"spread":false},{"title":"vl_tmove.cu <span style='color:#111;'> 75.72KB </span>","children":null,"spread":false},{"title":"bnorm_gpu.cu <span style='color:#111;'> 44.50KB </span>","children":null,"spread":false},{"title":"vl_imreadjpeg.cu <span style='color:#111;'> 43.02KB </span>","children":null,"spread":false},{"title":"nnconv_cudnn.cu <span style='color:#111;'> 23.12KB </span>","children":null,"spread":false},{"title":"im2row_gpu.cu <span style='color:#111;'> 19.84KB </span>","children":null,"spread":false},{"title":"vl_nnconv.cu <span style='color:#111;'> 17.25KB </span>","children":null,"spread":false},{"title":"nnbnorm_cudnn.cu <span style='color:#111;'> 16.76KB </span>","children":null,"spread":false},{"title":"data.cu <span style='color:#111;'> 14.44KB </span>","children":null,"spread":false},{"title":"pooling_gpu.cu <span style='color:#111;'> 13.36KB </span>","children":null,"spread":false},{"title":"vl_imreadjpeg_old.cu <span style='color:#111;'> 13.28KB </span>","children":null,"spread":false},{"title":"vl_nnconvt.cu <span style='color:#111;'> 13.25KB </span>","children":null,"spread":false},{"title":"datamex.cu <span style='color:#111;'> 13.22KB </span>","children":null,"spread":false},{"title":"roipooling_gpu.cu <span style='color:#111;'> 12.70KB </span>","children":null,"spread":false},{"title":"nnbilinearsampler_cudnn.cu <span style='color:#111;'> 11.88KB </span>","children":null,"spread":false},{"title":"bilinearsampler_gpu.cu <span style='color:#111;'> 11.78KB </span>","children":null,"spread":false},{"title":"datacu.cu <span style='color:#111;'> 10.02KB </span>","children":null,"spread":false},{"title":"vl_nnbnorm.cu <span style='color:#111;'> 9.63KB </span>","children":null,"spread":false},{"title":"vl_nnpool.cu <span style='color:#111;'> 9.32KB </span>","children":null,"spread":false},{"title":"nnpooling_cudnn.cu <span style='color:#111;'> 9.02KB </span>","children":null,"spread":false},{"title":"nnconv.cu <span style='color:#111;'> 8.78KB </span>","children":null,"spread":false},{"title":"nnbias_cudnn.cu <span style='color:#111;'> 8.37KB </span>","children":null,"spread":false},{"title":"vl_nnroipool.cu <span style='color:#111;'> 8.29KB </span>","children":null,"spread":false},{"title":"nnbnorm.cu <span style='color:#111;'> 8.15KB </span>","children":null,"spread":false},{"title":"nnfullyconnected.cu <span style='color:#111;'> 7.82KB </span>","children":null,"spread":false},{"title":"nnsubsample.cu <span style='color:#111;'> 7.11KB </span>","children":null,"spread":false},{"title":"vl_nnbilinearsampler.cu <span style='color:#111;'> 6.53KB </span>","children":null,"spread":false},{"title":"nnpooling.cu <span style='color:#111;'> 5.68KB </span>","children":null,"spread":false},{"title":"normalize_gpu.cu <span style='color:#111;'> 5.41KB </span>","children":null,"spread":false},{"title":"vl_taccummex.cu <span style='color:#111;'> 5.37KB </span>","children":null,"spread":false},{"title":"vl_nnnormalize.cu <span style='color:#111;'> 5.16KB </span>","children":null,"spread":false},{"title":"subsample_gpu.cu <span style='color:#111;'> 4.78KB </span>","children":null,"spread":false},{"title":"nnroipooling.cu <span style='color:#111;'> 4.69KB </span>","children":null,"spread":false},{"title":"nnbilinearsampler.cu <span style='color:#111;'> 4.51KB </span>","children":null,"spread":false},{"title":"nnnormalize.cu <span style='color:#111;'> 4.13KB </span>","children":null,"spread":false},{"title":"vl_cudatool.cu <span style='color:#111;'> 4.01KB </span>","children":null,"spread":false},{"title":"nnbias.cu <span style='color:#111;'> 3.91KB </span>","children":null,"spread":false},{"title":"copy_gpu.cu <span style='color:#111;'> 1.46KB </span>","children":null,"spread":false},{"title":"sharedmem.cuh <span style='color:#111;'> 3.97KB </span>","children":null,"spread":false},{"title":"googlenet_prototxt_patch.diff <span style='color:#111;'> 2.34KB </span>","children":null,"spread":false},{"title":".DS_Store <span style='color:#111;'> 6.00KB </span>","children":null,"spread":false},{"title":".DS_Store <span style='color:#111;'> 6.00KB </span>","children":null,"spread":false},{"title":"matconvnet.vcxproj.filters <span style='color:#111;'> 11.76KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 6B </span>","children":null,"spread":false},{"title":"tinythread.h <span style='color:#111;'> 20.72KB </span>","children":null,"spread":false},{"title":"mexutils.h <span style='color:#111;'> 19.21KB </span>","children":null,"spread":false},{"title":"fast_mutex.h <span style='color:#111;'> 6.78KB </span>","children":null,"spread":false},{"title":"imread_helpers.hpp <span style='color:#111;'> 20.91KB </span>","children":null,"spread":false},{"title":"nnconv_blas.hpp <span style='color:#111;'> 12.62KB </span>","children":null,"spread":false},{"title":"blashelper.hpp <span style='color:#111;'> 11.13KB </span>","children":null,"spread":false},{"title":"data.hpp <span style='color:#111;'> 6.99KB </span>","children":null,"spread":false},{"title":"nnbias_blas.hpp <span style='color:#111;'> 4.51KB </span>","children":null,"spread":false},{"title":"datacu.hpp <span style='color:#111;'> 4.30KB </span>","children":null,"spread":false},{"title":"cudnnhelper.hpp <span style='color:#111;'> 3.04KB </span>","children":null,"spread":false},{"title":"bnorm.hpp <span style='color:#111;'> 2.24KB </span>","children":null,"spread":false},{"title":"nnbnorm.hpp <span style='color:#111;'> 2.12KB </span>","children":null,"spread":false},{"title":"nnconv.hpp <span style='color:#111;'> 2.08KB </span>","children":null,"spread":false},{"title":"roipooling.hpp <span style='color:#111;'> 2.06KB </span>","children":null,"spread":false},{"title":"pooling.hpp <span style='color:#111;'> 1.97KB </span>","children":null,"spread":false},{"title":"nnbnorm_cudnn.hpp <span style='color:#111;'> 1.94KB </span>","children":null,"spread":false},{"title":"datamex.hpp <span style='color:#111;'> 1.88KB </span>","children":null,"spread":false},{"title":"......","children":null,"spread":false},{"title":"<span style='color:steelblue;'>文件过多,未全部展示</span>","children":null,"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明