搜索资源列表
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tms320c6000卷积的代码程序, -tms320c6000 convolutional code procedures tms320c6000 convolutional code procedures
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用matlab语言实现卷积码编码过程，有程序运行结果。-Matlab language used convolutional code encoding process, there are procedures for the results.
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该程序用matlab实现的，用于完成图形图像的卷积码编码。而卷积码是一种需要除了本组之外的信息来实现编解码。-The program achieved using matlab for complete graphic images encoded convolutional codes. The convolutional code is a need in addition to information outside the group to achieve codec.
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一种特定的卷积码的MATLAB仿真和结果-A specific convolutional code of MATLAB simulation and results
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这个是我找到的卷积神经网络在minist库上数字识别最好的结果，准确率99.5 ，比C++版本的更好。程序可以直接编译运行，但是因为要下载两个数据库可能非常慢，需要你修改一下代码跳过去。如果你对cnn很感兴趣，可以找我Q:3617 28654-This is what I found convolutional neural network minist library Digital Identification best results, the accuracy was 99.5 , be
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代码是基于CUDA环境下的图像卷积处理，基于Linux系统，文档中有makefile-Convolutional code on the image processing environment CUDA
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采用RS和1/2码率卷积码的级联码，实现高可靠性数字传输-Using RS and 1/2 rate convolutional code concatenated code, high reliability digital transmission
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用D-CNN的方法，即CNN卷积层加Fisher Vector做图像分类的MATLAB代码-Use D-CNN approach ( Fisher Vector follows results of CNN convolutional layer as the image feature) to classificate the image
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CNN卷积神经网络数字识别MATLAB代码-CNN convolutional neural network digital identification MATLAB code
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Code for CVPR15 paper Learning to Compare Image Patches via Convolutional Neural Networks
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This package allows researches to apply the described networks to match image patches and extract corresponding patches.
We tried to make the code
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CNT 跟踪算法源程序——Robust Visual Tracking via Convolutional Networks
without Training-code of the CNT algorithm —————Robust Visual Tracking via Convolutional Networks
without Training
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cnn网络从入门到精通，包括matlab工具箱源码解读，图形化解释，非常详细。学习卷积神经网络必读资料，-cnn network entry to the master, including source code matlab toolbox interpret graphical explain, in great detail. Convolutional neural network learning required reading,
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深度卷积神经网络超分辨，来自于ECCV2014一篇文章的代码，代码好用-Depth of the convolutional neural network super resolution, the ECCV2014 an article of the code, code easy to use
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用于图像分类的源代码，深度学习的应用，cnn卷积神经网络的使用，可以自己更换数据集或者调优，适合初学者使用！-For image classification of the source code, the application of in-depth learning, cnn convolutional neural network, you can replace the data set or tuning, suitable for beginners!
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卷积码是一种有记忆的编码,在任意给定的时间单元处,而且也与前m个输入有关,-Coding, convolutional code is a memory at any given time unit, but also related to m input before,
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VGG卷积神经网络练习，在matlab中使用vlfeat/matconvnet对图像进行去模糊的操作进而更好的识别图像(VGG Convolutional Neural Networks Practical)
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SRCNN代码实现。该代码使用三层卷积神经网络，进行图像的超分辨率重建，效果比双三次插值好很多(The code uses three layer convolutional neural network for image super-resolution reconstruction, the effect is much better than the double three interpolation.)
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卷积码是一种有记忆的编码,在任意给定的时间单元处,而且也与前m个输入有关,(Coding, convolutional code is a memory at any given time unit, but also related to m input before,)
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基于卷积神经网络的图像超分辨率重建，不含训练程序，包含已训练好的model !(Test code for Super-Resolution Convolutional Neural Networks (SRCNN))
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该代码实现了使用Matlab实现卷积神经网络来对图像进行去雾操作。(This code implements a convolutional neural network using Matlab to defog the image.)
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