Image Style Transfer Using Machine Learning

Autor: Dr. Bagam Laxmaiah
Rok vydání: 2022
Předmět:
Zdroj: International Journal for Research in Applied Science and Engineering Technology. 10:1187-1190
ISSN: 2321-9653
DOI: 10.22214/ijraset.2022.43990
Popis: The principle of Image style transfer is to define two distance functions, one that describes the content image and the other that describes the style Image. By using these content and Style Images[5][6] as inputs we will begetting the desired output which has the content image merged with style image. The output will be in the graphical model of the content image. In summary, we’ll take the base input image, a content image that we want to match, the style image that we want to match by undergoing the process of convolutional neural network [7] firstly the content image is undergoing the process of content loss and style image as style loss after content loss and style loss it will undergo the process of gram matrix and the final image will be formed. Keywords: Content Image, Style Image, Content Loss, Style Loss, Convolutional Neural Networks, Gram Matrix Deep Lab Semantic Segmentation.
Databáze: OpenAIRE