Add VGG networks.

data/models/README.md

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+# FMRI example models
+
+The following sections describe the models included in this repository,
+with attribution. The repository also includes deinplaced versions of
+the models, where relevant.
+
+## alexnet
+
+AlexNet trained on ILSVRC 2012, almost exactly as described in ImageNet
+classification with deep convolutional neural networks by Krizhevsky et
+al. in NIPS 2012. (Trained by Evan Shelhamer @shelhamer)
+
+## caffenet
+
+AlexNet trained on ILSVRC 2012, with a minor variation from the version
+as described in ImageNet classification with deep convolutional neural
+networks by Krizhevsky et al. in NIPS 2012. (Trained by Jeff Donahue
+@jeffdonahue)
+
+## vgg-16
+
+The model is an improved version of the 16-layer model used by the VGG
+team in the ILSVRC-2014 competition. The details can be found in the
+following [arXiv paper](http://arxiv.org/pdf/1409.1556):
+
+    Very Deep Convolutional Networks for Large-Scale Image Recognition
+    K. Simonyan, A. Zisserman
+    arXiv:1409.1556
+
+Please cite the paper if you use the model.
+
+In the paper, the model is denoted as the configuration `D` trained with
+scale jittering. The input images should be zero-centered by mean pixel
+(rather than mean image) subtraction. Namely, the following BGR values
+should be subtracted: `[103.939, 116.779, 123.68]`.
+
+
+## vgg-19
+
+The model is an improved version of the 19-layer model used by the VGG
+team in the ILSVRC-2014 competition. The details can be found in the
+following [arXiv paper](http://arxiv.org/pdf/1409.1556):
+
+    Very Deep Convolutional Networks for Large-Scale Image Recognition
+    K. Simonyan, A. Zisserman
+    arXiv:1409.1556
+
+Please cite the paper if you use the model.
+
+In the paper, the model is denoted as the configuration `E` trained with
+scale jittering. The input images should be zero-centered by mean pixel
+(rather than mean image) subtraction. Namely, the following BGR values
+should be subtracted: `[103.939, 116.779, 123.68]`.