Vectorized implementation of convolutional neural networks (CNN) in Matlab for both visual recognition and image processing. It's a unified framework for both high level and low level computer vision tasks. The code is on Github.
How to run demos
For MNIST, you can launch this script to use a pre-trained model. For training, just launch this script. You will get sensible results within seconds.
For image denoise, launch this script to see the denoise result by pre-train models. For training, you need to generate the data yourself since the data used in the training is large. Please do the following steps to generate data: a) download MIT saliency dataset from here and put all the image files here; b) launch this script to generate training data; c) launch this script to generate validation data; d) launch this script to start the training.
Hardware/software requirements
Matlab 2014b or later, CUDA 6.0 or later(currently tested in Windows 7).
A Nvidia GPU with 2GB GPU memory or above (if you would like to run on GPU). You can also train a new model without a GPU by specifying "config.compute_device = 'CPU';" in the config file (e.g. mnist_configure.m).