Deep learning models

Deep learning is being applied to more and more domains and industries. From driverless cars, to playing Go, to generating images' music, there are new deep learning models coming out every day. Here we go over several popular deep learning models. Scientists and developers are taking these models and modifying them in new and creative ways. We hope this showcase can inspire you to see what is possible.

NEURAL STYLE :-
If you have ever used Instagram or Snapchat, you are familiar with using filters that alter the brightness, saturation, contrast, and so on of your images. Neural style, a deep learning algorithm, goes beyond filters and allows you to transpose the style of one image, perhaps Van Gogh’s “Starry Night,” and apply that style onto any other image.

WORKING:-
Neural style uses a deep neural network in order to separate and recombine the content and style of any two images. It is one of the first artificial neural networks (ANNs) to provide an algorithm for the creation of artistic imagery.
The model is given two input images, one that that will be used for styling, the other for content. At each processing stage in the convolutional neural network’s (CNN) hierarchy, the images are broken into a set of filtered images. While the number of different filters increases along the processing hierarchy, the overall size of the filtered images is reduced, leading to a decrease in the total number of units per layer of the network.