Once we have images for every sense, we can turn these images into feature representations us-ing a convolutional neural network (CNN).
we used the VGG 16-layer architecture (VG-GNet) trained on 1.2M images of the 1000 class ILSVRC 2012 object classification dataset, a subset of ImageNet (Simonyan and Zisserman, 2014).