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Robust AI Digital Copyright Protection Scheme
Balika J Cheliah1, Srushti Bompelli2, Madhumita Sampath3, Maithili Ghogre4, Aravind Ajithkumar5

1Balika J Cheliah, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (TamilNadu), India.

2Srushti Bompelli, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (TamilNadu), India.

3Madhumita Sampath, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (TamilNadu), India.

4Maithili Ghogre, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (TamilNadu), India.

5Aravind Ajithkumar, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (TamilNadu), India.

Manuscript received on 04 April 2019 | Revised Manuscript received on 11 April 2019 | Manuscript Published on 26 April 2019 | PP: 100-104 | Volume-8 Issue-6S April 2019 | Retrieval Number: F60310486S19/19©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The way we watch and consume media is constantly changing. With growing Web Technologies, creation, marketing and distribution of media content is fast changing. This opens up immense opportunities for piracy and redistribution. One can find several ways to share media content online like Social Networking Portals, Free Cloud Spaces and Drives, emails, chats etc. Due to the sheer volume of information and content available on the Internet, it becomes impossible to detect and stop piracy manually. Thus, the objective of this paper is to propose a solution to fight piracy using Artificial Intelligence and Machine Learning. The proposed system leverages Artificial Intelligence and Machine Learning by using content monitoring solutions that search and identify pirated content on the internet. This is done by identifying the original source of distributed content based on the visual information present in the image such as the broadcaster logo. The paper covers practical issues around building a system with its workflow, training and performance.

Keywords: Artificial Intelligence, Deep Learning, Media, logo Detection.
Scope of the Article: Deep Learning