I am new to matlab and my project requires 1D Convolutional Neural Network. Can anyone tell me how to design 1D CNN in matlab? Does it require any special hardware? Refrence to some blogs will be really helpful.
Thank you.
As I know CNN implementation requires GPU. Matlab 2016 version have some inbuilt function but requires GPU installed to work. Python and tensorflow works great and quick , I would like you suggest to try those than Matlab.
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I have a structure for my CNN that will be used in image enhancement. and I want to know how to use Caffe package in Matlab to design and train the network. I don't need to import pretrained network from Caffe as I have a specific structure for the CNN. Does any one have a link or example that guide me on how to do that? Any help will be appreciated.
The Caffe official documentation has a simple example showcasing basic interfaces for Matlab including adding conv layers to the network:
http://caffe.berkeleyvision.org/tutorial/interfaces.html#matlab
Once you get the basics for matlab, the interfaces are mostly similar to python.
Hope that helps
I have been trying to figure this out for some time but i am still a bit unsure. Does the PyTorch pre-trained VGG-16 (torchvision model) have exactly the same weights as the MATLAB pre-trained VGG-16?
If you are interested to find out, just take the norm of the weights in both libraries. I think they should be same.
In the lectures we only mention how to train the RBF network with Gausian function and how to use the "newrb" tool box in Matlab. But in the assignemnet I need to create my own RBF network which using the NN toolbox is forbidden. Basically I not even know how to start it and our professor not willing to provide any information.
With some tips I have write my own program but the performance is very bad, I am wonder if any one can give me some helpful tutorial or guides that how to create the RBF network with Gaussian function without using NN toolbox.
I have used k-means to obtain the centers and gaussian function to caculuate the weights, the main probrlem is that I have no idea how to design the method that transform the Input matrix to the RBF matrix. Hope you can help.
This is clearly homework, and it's not clear what your question is. But I think you are wondering how to create the Gram matrix. If so, see:
http://en.wikipedia.org/wiki/Gramian_matrix
You should have the math for how to do each step in your textbook and/or notes.
I tried with GPUmat, but the neural network toolbox from mathworks does´t support it. Otherwise I must change the nn-toolbox by myself. But it´s too hard for me. Any suggestion for me?
I don't know whether this will accelerate the Neural Network Toolbox in particular, but the Mathworks now offers CUDA GPU support via the Parallel Computing Toolbox:
http://www.mathworks.com/discovery/matlab-gpu.html?s_cid=HP_MI_tech_gpu
Matlab provides its own toolbox for training neural networks on GPU, see here.
As an author, I also advice to use my toolbox ConvNet, that uses kernels of Alex Krizhevsky's library cuda-convnet2. It also has pure CPU and Matlab versions, that work identically. There is also another toolbox for Matlab, called MatConvNet, but I have not checked it.
I have a homework to classify multi-class images with Support Vector Machines. I am not allowed to use any toolbox, I have to write SVM code by my self. I have to implement it in MATLAB. Since I am not familiar with MATLAB, I have some troubles about implementing.
Can you suggest me any pseudocode or paper that explains the svm implementation basically? I mean I know the theory of SVM but I am just not good at programming. Or any SVM code might be very helpful!
Thank you for your help in advance.
I like using LibSVM library. On its web pages you can find some useful hints and descriptions of the SVM. There is also beginner's guide to SVM classification. The source code itself should be available as well.
http://www.csie.ntu.edu.tw/~cjlin/libsvm/