Building of Informatics, Technology and Science
Vol 3 No 3 (2021): December 2021

Manipulasi Gambar dengan Transfer Gaya Menggunakan Convolutional Neural Network

Khalida, Rakhmi (Unknown)
Ramdhania, Khairunnisa Fadhilla (Unknown)



Article Info

Publish Date
31 Dec 2021

Abstract

Recently computers have been able to produce photographs that allow users to compose selfies with van Gogh paintings. Inspired by the power of convolutional neural networks (CNN), he first learned how to use CNN to reproduce famous painting styles combined with self-portrait images. The method used is called a neural network transfer. However, early versions of neural networks had optimization problems, requiring hundreds or thousands of iterations to transfer forces combined with a single image. To overcome this in-efficiency, researchers developed the CNS-style PerStyle-Per-Model (PSPM) transfer method. The development of force transfer using a deep neural network is also called NST by training the VGG-16 model to change any image in one feed, foward propagation. A trained model can adjust to any drawing mode with just one iteration instead of thousands of iterations over the network and to get the most objective possible style of transfer

Copyrights © 2021






Journal Info

Abbrev

bits

Publisher

Subject

Computer Science & IT

Description

Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. ...