An image is fed to the network, which is trained to recognize different categories for the images in the ImageNet dataset which contain 1.2 million images across 1000 categories. The final layer builds a classifier from these features and the output is the most likely category for the image.ĭeep dream works by reversing this process. segments of the image that discern the types of images. Initial layers detect edges and corners, these features are then fed into next layers which combine them to produce features that make up the image e.g. CNNs work by progressively extracting higher-level features from the image at the successive layers of the network. The information moves from one layer to the next. A deep neural network has an input layer, where the data is fed into, an output layer, which produces the prediction for each data point, and a lot of layers inbetween. This marks the begining of inceptionistic art creation using neural networks.ĭeep convolution neural networks (CNNs) have been very effective in image recognition problems. It was later confirmed that this image was indeed generated by a neural network after Google described the mechanism for generation of such images, they called it deepdream and released their code for anyone to produce these images. There was a lot of speculation about the validity of such a claim. The following image, known as dog-slug, was posted on Reddit and was reported to be generated by a convolution neural network.
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