Video depicting all the layers of a deep nerual network. The
Convolutional Neural Network has been pretrained with ImageNet. The
first input image is a picture of myself and at every step the
image is zoomed with a ratio of 0.05. At every step the actual
input image (frame) is forwarded to the actual hidden layer. The
error is set to be the same representation in order to maximize all
its activations. Then, a backward pass is computed to modify the
input image. After 100 iterations of zooming in one layer, the next
layer is used. See more in my Aalto
personal web-page
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