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We would be providing input as content image and style image to the system. then based on the feature mapping it will extract the features from Content Image as well as Style Image and those features extracted images would be called Content representation and Style representation respectively. The difference between original content image and target image is content loss and difference in original style image and target image is called style loss. When we combine these two we get total loss and we need to minimize it to get high quality target image

Figure 3 We would be providing input as content image and style image to the system. then based on the feature mapping it will extract the features from Content Image as well as Style Image and those features extracted images would be called Content representation and Style representation respectively. The difference between original content image and target image is content loss and difference in original style image and target image is called style loss. When we combine these two we get total loss and we need to minimize it to get high quality target image

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How would it look if we chose to paint this Turtle purely in this style? Something like this?
How would it look if we chose to paint this Turtle purely in this style? Something like this?
Fig. 2. Resultant image of Fig 1's content and Fig 2's style. Fig. 1. Style Image and content image
Fig. 2. Resultant image of Fig 1's content and Fig 2's style. Fig. 1. Style Image and content image
Fig. 4. Some of the sample images and their result we achieved Recently there have been multiple researches done on the neural style transfer. and as the computational power is becoming cheaper and faster, and as more optimized and fast deep learning algorithms are discovered we are hoping to see more research on this topic. And its use in other related fields also
Fig. 4. Some of the sample images and their result we achieved Recently there have been multiple researches done on the neural style transfer. and as the computational power is becoming cheaper and faster, and as more optimized and fast deep learning algorithms are discovered we are hoping to see more research on this topic. And its use in other related fields also
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Computer ScienceArtificial Intelligence
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