IMAGE STYLE TRANSFER USING MACHINE LEARNING.

The principle of Image style transfer is todefine 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 be getting the desired output which has the content image merged with style ima...

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Detalles Bibliográficos
Publicado en:Proteus Vol. 13; no. 10; pp. 35 - 41
Autores principales: Laxmaiah, Bagam, Narasimharao, Jonnadula, Maringanti, Abhigna, Govindula, SriTeja, Dharamsoth, Suresh
Formato: Artículo
Publicado: Proteus Oct2022
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:The principle of Image style transfer is todefine 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 be getting the desired output which has the content image merged with style image. The ouput will be in the graphical model of the content image. In summary, we'll take the base input image, a contentimage 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 lossit will undergo the process of gram matrix and the final image will be formed.