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- Vol. 4 Issue 3
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Fake Image Detection on Social Media using CNN Algorithm
Authors
1234 B.Tech Students, Department of Computer Science & Engineering, Institute of Technology and Management, GIDA, Gorakhpur,India. 5Assistant Professor, Department of Computer Science & Engineering, Institute of Technology and Management, GIDA, Gorakhpur,India.
Article Information
- DOI
- No DOI
- Published In
- Volume 4, Issue 3 (2023)
- Published Online
- May-June 2023
- Pages
- 01-05
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
References
1. G.Mohamed Sikandar, "100 SocialMedia Statistics You must know,"[online] Available at: https://blog.statusbrew.com/socialmediastatistics-2018-for-business/ [Accessed 02 Mar 2019].
2. Kit Smith,"49 Incredible InstagramStatistics,". Brandwatch. [online] Available at:https://www.brandwatch.com/blog/inst agramstats/ [Accessed 10 May 2019].
3. Li, W., Prasad, S., Fowler, J. E., &Bruce, L. M. (2012). Localitypreserving dimensionality reduction and classification
for hyperspectral image analysis. IEEE Transactions on Geoscience and Remote Sensing, 50(4), 1185–1198.
4. K. Ravi, (2018). Detecting fake imageswith Machine Learning. HarkuchJournal
5. L. Zheng, Y. Yang, J. Zhang, Q. Cui, X.Zhang, Z. Li, et al. (2018). TICNN:Convolutional Neural Networks for Fake News Detection.
United States
6. S. Aphiwongsophon, & P. Chongstitvatana, (2017). DetectingFake News with Machine Learning Method. Chulalongkorn University,
Department of Computer Engineering, Bangkok, Thailand.
7. M. D. Ansari, S. P. Ghrera, & V. Tyagi,(2014). Pixel-based image forgery detection: A Review. IETE Journal of Education, 55(1), 40–
46.
8. Y. Li, & S. Cha, (2019). Face Recognition System. arXiv preprint arXiv:1901.02452.
9. R. Saracco, (2018). Detecting fakeimages using artificial intelligence. IEEE Future Directions.
2. Kit Smith,"49 Incredible InstagramStatistics,". Brandwatch. [online] Available at:https://www.brandwatch.com/blog/inst agramstats/ [Accessed 10 May 2019].
3. Li, W., Prasad, S., Fowler, J. E., &Bruce, L. M. (2012). Localitypreserving dimensionality reduction and classification
for hyperspectral image analysis. IEEE Transactions on Geoscience and Remote Sensing, 50(4), 1185–1198.
4. K. Ravi, (2018). Detecting fake imageswith Machine Learning. HarkuchJournal
5. L. Zheng, Y. Yang, J. Zhang, Q. Cui, X.Zhang, Z. Li, et al. (2018). TICNN:Convolutional Neural Networks for Fake News Detection.
United States
6. S. Aphiwongsophon, & P. Chongstitvatana, (2017). DetectingFake News with Machine Learning Method. Chulalongkorn University,
Department of Computer Engineering, Bangkok, Thailand.
7. M. D. Ansari, S. P. Ghrera, & V. Tyagi,(2014). Pixel-based image forgery detection: A Review. IETE Journal of Education, 55(1), 40–
46.
8. Y. Li, & S. Cha, (2019). Face Recognition System. arXiv preprint arXiv:1901.02452.
9. R. Saracco, (2018). Detecting fakeimages using artificial intelligence. IEEE Future Directions.
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