Detection of Fake Doctored Images used to Circulate Fake News
R. Kayalvizhi1, Abhisek Bharadwaz2, Monisankar Baruah3
1Dr.R. Kayalvizhi*, Assistant Professor, Department of Computer Science And Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai.
2Mr. Abhisek Bharadwaz, Student, B.Tech, Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai.
3Mr. Monisankar Baruah , Student, B. Tech, Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai.
Manuscript received on April 20, 2020. | Revised Manuscript received on April 29, 2020. | Manuscript published on May 10, 2020. | PP: 1031-1036 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5747059720/2020©BEIESP | DOI: 10.35940/ijitee.G5747.059720
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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: Over the few years the world has seen a surge in fake news and some people are even calling it an epidemic. Misleading false articles are sold as news items over social media, whatsapp etc where no proper barrier is set to check the authenticity of posts. And not only articles but news items also contain images which are doctored to mislead the public or cause sabotage. Hence a proper barrier to check for authenticity of images related to news items is absolutely necessary. And hence classification of images(related to news items) on the basis of authenticity is imminent. This paper discusses the possibilities of identifying fake images using machine learning techniques. This is an introduction into fake news detection using the latest evolving neural network models.
Keywords: Machine Learning(ML), Neural Networks, Fake News, Fake Images.
Scope of the Article: Machine Learning