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Hello Reader,
Welcome to another edition of the AIFEE newsletter!
Another week, another Machine Learning topic!
Image style transfer is an approach that you can apply for image painting, where the goal is to extract the style from one image and apply it to a second image while preserving the content of this second image.
In order to achieve this, the style of an image needs to be defined.
In fact, the style of an image is very much related to its texture. So by using texture extraction methods, we are essentially extracting the style of an image. These methods are called Visual Texture Modeling methods. There are 2 types of these methods :
In order to apply this style on an image, we can use image reconstruction techniques. There are 2 types of these techniques as well:
Convolutional neural networks can be used for both Visual Texture Modeling and Image Reconstruction.
One of the fairly simple approaches to do style transfer in images is by using the approach described in the paper “A Neural Algorithm of Artistic Style”.
What you need :
What to do:
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The image above I created using open source code from a tutorial provided by Tensorflow.
The previous approach gives some great results from an artistic perspective, but the downside is that it’s too long.
Every image has to go through a set of iterations where there is extraction of the content and the style of two images and then there is an optimization process to make one image’s style close to another one’s.
Because of this hurdle, another approach has been proposed in the literature. With this method, there are two neural networks working together.
One network extracts the style from the style image. The other network has two inputs : the content image and the output of the previous network.
With this approach, the full system learns representations of painting styles from a large dataset during the training phase.
At test time, the network directly extracts the style from the style images and applies it to the content image. No optimization needed!
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by Nour Islam Mokhtari from pycad.co
👉 Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | 💡 The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!
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