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 |
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Description: This project provides matlab class for implementation of convolutional neural networks. This networks was created by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot navigation and others
This release includes sample of handwritten digits recognition using CNN. Platform: |
Size: 551936 |
Author:ssss |
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Description: In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. With the weights of the trained neural networks there are created kernel windows used for feature extraction in a 3-stage algorithm. I present experimental results illustrating the efficiency of the proposed approach. I use a database of 796 images of 159 individuals from Reims University which contains quite a high degree of variability in expression, pose, and facial details.
Platform: |
Size: 15069184 |
Author:Razvan |
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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: 此文件包包含用卷积神经网络识别手写输入的识别程序，数据可从MNIST下载-This release includes sample of handwritten digits recognition using CNN. If you just want to try it run cnet_tool. You ll see a simple GUI. It loads pretrained convolutional neural net from cnet.mat and recognizes image of digit either painted in painting area or downloaded from MNIST database. Platform: |
Size: 637952 |
Author:Hunter |
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Description: 端至端卷积神经网络的文字识别,代码演示包.
它包含我们的论文中使用的所有主要组成部分: kmeans无监督特征学习 + 卷积神经网络(CNN)-This is a demo package of the code we used for our paper, "End-to-End
Text Recognition with Convolutional Neural Networks", T. Wang, D. Wu,
A. Coates, A. Ng, in ICPR 2012.
The package is provided to facilitate understanding of the algorithms
used in our paper. It contains demos to all the major components of our
end-to-end system. Because of speed considerations, the CNN
architectures as well as dataset sizes provided in this package are
much smaller than the actural ones used in the paper, although the
algorithms themselves are identical. We also provide our trained models
together with code to reproduce major results reported in our paper. Platform: |
Size: 61051904 |
Author:twang |
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Description: 深度学习（Deep learning）matlab工具包-`NN/` - A library for Feedforward Backpropagation Neural Networks
`CNN/` - A library for Convolutional Neural Networks
`DBN/` - A library for Deep Belief Networks
`SAE/` - A library for Stacked Auto-Encoders
`CAE/`- A library for Convolutional Auto-Encoders
`util/`- Utility functions used by the libraries
`data/`- Data used by the examples
`tests/`- unit tests to verify toolbox is working
Platform: |
Size: 14777344 |
Author:Xiaojuan Jiang |
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Description: 人体骨骼的关键点提取，总共十四个点，使用卷积神经网络。(The key points of human skeleton are extracted from a total of fourteen points using convolutional neural networks.) Platform: |
Size: 24378368 |
Author:zwzwzzwz |
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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: Watermarking is an operation of embedding infor-
mation into an image in a way that allows to identify ownership
of the image despite applying some distortions on it. In this
paper, we present a novel end-to-end solution for embedding and
recovering the watermark in the digital image using convolutional
neural networks. We propose a spreading method of the message
over the spatial domain of the image, hence reducing the local
bits per pixel capacity and significantly increasing robustness. To
obtain the model we use adversarial training, apply noiser layers
between the encoder and the decoder, and implement a precise
JPEG approximation. Moreover, we broaden the spectrum of
typically considered attacks on the watermark and we achieve
high overall robustness, most notably against JPEG compression,
Gaussian blur, subsampling or resizing. We show that an appli-
cation of some attacks could increase robustness against other
non-seen during training distortions across one group of attacks
— a proper grouping of the attacks according to their scope
allows to achieve high general robustness Platform: |
Size: 774757 |
Author:bamzi334 |
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Search - convolutional neural