• V Sathya

Abstract—User Interaction is increased in Digital Content providers by utilizing custom visual representation to aid recommend-er systems. Previously this was either done with systems that had a large amount of static media store. The proposed model utilizes convolutional neural networks to create a self generating media store which is then served as a micro- service endpoint to the end developer. We aim to propose a fully fledged L2 cache augmented service to aid the problem of custom styled content representation media distribution to increase user interaction.

AI, ML, SAAS, Cloud Computing

"Dynamic Serving of Custom Styled Content Representation using Style Transfer in Convolutional Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.665-669, April-2019, Available :http://www.jetir.org/papers/JETIR1904E98.pdf

"Dynamic Serving of Custom Styled Content Representation using Style Transfer in Convolutional Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp665-669, April-2019, Available at : http://www.jetir.org/papers/JETIR1904E98.pdf