Neural Style Transfer refers to a class of software algorithms that manipulate digital images, or videos, in order to adapt the appearance or visual style of another image. Neural Style Transfer algorithms are characterized by their use of deep neural networks for the sake of image transformation. Simply put output image retains the core elements of the content image but appears to be painted in the style of the style reference image.
“Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it’s worth it in the end because once you get there, you can move mountains.”
― Steve Jobs
Content-based image recognition (CBIR) refers to the retrieval of similar images from the dataset by providing an image as a query. It is equivalent to providing the human vision to the computer. Let’s consider a scenario. …