Fast Style Transfer is a deep learning-based technique used to transfer the style of one image to another quickly. It is a technique used in computer vision and image processing.The process involves training a neural network to recognize and extract the style of an image, and then applying that style to a different content image. The neural network is typically trained on a large dataset of images with different styles.
Retrieval refers to the process of retrieving information from a collection of documents or data based on a user's query. In other words, when a user enters a search query, the search engine retrieves all the relevant documents or data from its database that match the query. The retrieved documents are usually presented to the user in a ranked order based on their relevance to the query.
Ranking, on the other hand, refers to the process of ordering the retrieved documents based on their relevance to the user's query. The ranking algorithm takes into account various factors such as the frequency and location of the search terms in the document, the document's popularity and quality, and other factors to determine the order in which the documents are presented to the user.
