Deep Dream uses this same idea, with a couple of simple differences: The Deep Dream algorithm is nearly just like the convnet filter-visualization technique, consisting of running a convnet in reverse: doing gradient ascent on the input to the convnet so as to maximize the activation of a selected filter in an upper layer of the convnet. It quickly became an online sensation because of the trippy pictures it could generate, filled with algorithmic pareidolia artifacts, bird feathers, and dog eyes - a byproduct of the very fact that the Deep Dream convnet was trained on Image Net, where dog breeds and bird species are vastly overrepresented. It had been first released by Google within the summer of 2015, as an application written using the Caffe deep-learning library. Descriptionĭeep Dream is an inventive image-modification technique that uses the representations learned by convolutional neural networks. Google’s program spread the term (deep) “dreaming” to ask the generation of images that produce desired activations during a trained deep network, and therefore the term now refers to a set of related approaches. He used a convolutional neural network to seek out and enhance patterns in images via algorithmic pareidolia by creating a dream-like hallucinogenic appearance within the deliberately over-processed images. Deep Dream is a computer vision program created by Google engineer Alexander Mordvintsev.

Deep dreamer app