Developing an App to Generate Artistic Deep Dream Images based on a Deep Learning Framework

Tan, Weng Kun (2020) Developing an App to Generate Artistic Deep Dream Images based on a Deep Learning Framework. [Final Year Project Report] (Unpublished)

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Abstract

This study is concerned about the DeepDream Generator. DeepDream Generator is an app that are able to transforms ordinary photo into artistic images. Nowadays, people tend to do the things all the same ways without thinking out of box. This is because there is no platform for them to express themselves and creating art. It is important to exposed to art since small because being exposed to art can helps in release stress and increase creativity thinking. With problem statement, the objective is design and develop an app that implements the framework for the generation of creative and artistic images based on a user-selected photographic medium. Hence, the aim of this paper is to describe and demonstrate the development Deep Dream Generator for provides targeted users a free platform to express themselves, release stress and even able to help them improve their creativity. The methodology chosen to use in this study is the rapid prototyping methodology (RAD). Lastly, the conclusion and future work will be discussed at the end of this project.

Item Type: Final Year Project Report
Additional Information: Project Report (BSc.) -- Universiti Malaysia Sarawak, 2020.
Uncontrolled Keywords: DeepDream Generator, rapid prototyping methodology (RAD), artistic images, creativity thinking.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Gani
Date Deposited: 04 Mar 2021 04:17
Last Modified: 15 Mar 2024 07:49
URI: http://ir.unimas.my/id/eprint/34678

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