DCN_AlexNet - a deep convolutional network for image classification
Dean Pospisil and Wyeth Bair
UNDER CONSTRUCTION - Aug 2017
This Topic Page describes how to run the DCN_AlexNet model from a linux (or Mac OS X) command line using the WM model command. You will first need to download and compile the WM software (follow the iModel Download link).
This implementation of AlexNet provides access to a pre-trained model that can be tested with visual stimuli. Responses from all of the internal units can be studied. Training has not been implemented here, but is available from other sources, for example the Caffe deep learning framework.
Measuring responses to a test image. The following command will run the DCN_AlexNet model on a test image of a kitten:where the following parameter and data files are required:wm mod DCN_AlexNet.moo image.stm all_center.rsp
The output is written to a file named "zz.nd," which contains response values for each of the units at the spatially centered position in the network. The values can be extracted to a text file with the following command:nda resp.nda zz.nd out.txt