Description: CNN Class, ver 0.72.
Change log:
Ver 0.72:
Sample GUI added, demonstrating use of convolutional network for handwriten digits recognition.
Training runs 20 faster.
Ver 0.71:
Bug fix: training was stoped after 1 epoch.
Ver 0.70:
First release.
This project provides matlab class for implementation of convolutional neural networks. -CNN Class, ver 0.72.
Change log:
Ver 0.72:
Sample GUI added, demonstrating use of convolutional network for handwriten digits recognition.
Training runs 20 faster.
Ver 0.71:
Bug fix: training was stoped after 1 epoch.
Ver 0.70:
First release.
This project provides matlab class for implementation of convolutional neural networks. Platform: |
Size: 555008 |
Author:narendra |
Hits:
Description: 卷积神经网络的Csharp版本，已经编译成windowsAPI库，根据Mike的源代码改写而成。供研究卷积神经网络CNN的人使用。-Csharp version convolutional neural network has been compiled into windowsAPI library, according to the source code adapted from Mike. CNN convolutional neural networks for research of the people. Platform: |
Size: 3759104 |
Author:LiuKe |
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Description: 卷积码的编码器是由一个有k个输入端、n个输出端、m节移位寄存器所构成的有限状态的有记忆系统，通常称它为时序网络。-A convolutional code encoder is composed of a k-th input terminal of the n output terminals, m section shift register constituted by a finite state memory system, the usually call timing network. Platform: |
Size: 9216 |
Author:赵迪 |
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Description: 常用神经网络算法，以及原理实现。。。包括MLP神经网络、卷积神经网络-Common neural network algorithm, as well as the principle of implementation... Including MLP neural network, convolutional neural network, etc. Platform: |
Size: 4140032 |
Author:snow |
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Description: 基于深度学习的图像超分辨率算法。
参考论文 Learning a Deep Convolutional Network for Image Super-Resolution (ECCV 2014)
-Super resolution based on deep learning
Refer to Learning a Deep Convolutional Network for Image Super-Resolution (ECCV 2014) Platform: |
Size: 5583872 |
Author:云和山 |
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Description: 手写汉字识别，数据集训练，MNIST，Deep Convolutional Network识别手写汉字(Handwritten Chinese character recognition, data set training, MNIST, Deep Convolutional Network) Platform: |
Size: 1024 |
Author:PopYo |
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Description: 是《Learning a Deep Convolutional Network for Image Super-Resolution》文章相关的MATLAB代码，可以利用训练好的字典，通过CNN实现超分辨率重建(SR)的功能。(Matlab demo code for "Learning a Deep Convolutional Network for Image Super-Resolution" (ECCV 2014) and "Image Super-Resolution Using Deep Convolutional Networks" (arXiv:1501.00092). This Matlab version is a re-implementation, and is for the ease of understanding the algorithm. This code is not optimized, and the speed is not representative.) Platform: |
Size: 7032832 |
Author:陌丶小离 |
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Description: matlab，深度学习工具箱，经典的卷积神经网络，共有两层卷积层。输入为28*28*1的图片(Matlab, the deep learning toolbox, the classic convolution neural network, has two volumes of layers. A picture entered into 28*28*1) Platform: |
Size: 15171584 |
Author:munchkin329 |
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Description: 这是Convolutional Network的一个实现。此外，它提供了一些可视化更高级别特征的工具，并演示了原始输入图像重建的一个例子。(This is one of the implementations of Convolutional Network. In addition, it provides some tools for visualizing higher level features, and demonstrates an example of original input image reconstruction.) Platform: |
Size: 52224 |
Author:wuxiaolang |
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Description: 这篇文章是CVPR2017的oral，非常厉害。文章提出的DenseNet（Dense Convolutional Network）主要还是和ResNet及Inception网络做对比，思想上有借鉴，但却是全新的结构，网络结构并不复杂，却非常有效！众所周知，最近一两年卷积神经网络提高效果的方向，要么深（比如ResNet，解决了网络深时候的梯度消失问题）要么宽（比如GoogleNet的Inception），而作者则是从feature入手，通过对feature的极致利用达到更好的效果和更少的参数。(This article is the oral of CVPR2017, very powerful. This paper DenseNet (Dense Convolutional Network) mainly and ResNet and Inception Network do contrast, reference ideas, but he is a new structure, Network structure is not complicated, but very effective! As is known to all, in the last year or two, the direction of improving the effect of convolutional neural network is either deep (such as ResNet, which solves the gradient disappearance problem in deep network) or wide (such as GoogleNet's Inception), while the author starts from feature and achieves better effect and fewer parameters through the extreme utilization of feature) Platform: |
Size: 30720 |
Author:123xy |
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Search - Convolutional network