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Research Article
Fake Image Detection on Social Media usingCNN Algorithm
Aakash Singh1
Deepak Verma2
Km Annu Singh3
Km Pinki Yadav4
Sunil Yadav5
1234 Computer Science and Engineering, Institute of Technology and Management, Gorakhpur, India. 5Assistant Professor, Computer Science and Engineering, Institute of Technology and Management, Gorakhpur, India.
Published Online: November-December 2022
Pages: 83-85
Cite this article
No DOIReferences
1. G.Mohamed Sikandar, "100 Social Media Statistics You must know," [online] Available at: https://blog.statusbrew.com/social-
mediastatistics-2018-for-business/ [Accessed 02 Mar 2019].
2. 2.Damian Radcliffe, Amanda Lam, "Social Media in the Middle
East,"[online]Available:https://www.researchgate.net/publication/32318
5146_Social_Media_in_the_Middle_East_The_Story_of_2017 [Accessed 06 Feb 2019].
3. 3.Strigl, K. Kofler, & S. Podlipnig, (2010). Performance of GPU-based CNN model.
4. Li, W., Prasad, S., Fowler, J. E., & Bruce, L. M. (2012).Hyperspectral image analysisusing dimensionality reduction and
classification with locality preservation.
a. Krizhevsky, I. Sutskever, & G. E. Hinton, (2012). Using deep convolutionalneural networks to classify images.
5. K. Ravi, (2018). Detecting fake images with Machine Learning. Harkuch Journal.
6. ] J. Bunk, J. Bappy, H. Mohammed, T. M. Nataraj, L., Flenner, A., Manjunath, B., et al. (2017)Combining deep learning with
resampling characteristics to recognise and locate fake images. Electrical and Computer Engineering Department from University of
California at USA.
7. R. Raturi, (2018).Implementing Machine Learning to Spot Fake Accounts on Social Networks.50(4), 1185–1198 of the IEEE
Transactions on Geoscience and Remote Sensing.
8. M. Villan, A. Kuruvilla, K. J. Paul, & E. P. Elias, (2017). Fake Image Detection Using Machine Learning.
9. D.-H. Kim, & H.-Y. Lee, (2017). Image Manipulation Detection using Convolutional Neural Network.
mediastatistics-2018-for-business/ [Accessed 02 Mar 2019].
2. 2.Damian Radcliffe, Amanda Lam, "Social Media in the Middle
East,"[online]Available:https://www.researchgate.net/publication/32318
5146_Social_Media_in_the_Middle_East_The_Story_of_2017 [Accessed 06 Feb 2019].
3. 3.Strigl, K. Kofler, & S. Podlipnig, (2010). Performance of GPU-based CNN model.
4. Li, W., Prasad, S., Fowler, J. E., & Bruce, L. M. (2012).Hyperspectral image analysisusing dimensionality reduction and
classification with locality preservation.
a. Krizhevsky, I. Sutskever, & G. E. Hinton, (2012). Using deep convolutionalneural networks to classify images.
5. K. Ravi, (2018). Detecting fake images with Machine Learning. Harkuch Journal.
6. ] J. Bunk, J. Bappy, H. Mohammed, T. M. Nataraj, L., Flenner, A., Manjunath, B., et al. (2017)Combining deep learning with
resampling characteristics to recognise and locate fake images. Electrical and Computer Engineering Department from University of
California at USA.
7. R. Raturi, (2018).Implementing Machine Learning to Spot Fake Accounts on Social Networks.50(4), 1185–1198 of the IEEE
Transactions on Geoscience and Remote Sensing.
8. M. Villan, A. Kuruvilla, K. J. Paul, & E. P. Elias, (2017). Fake Image Detection Using Machine Learning.
9. D.-H. Kim, & H.-Y. Lee, (2017). Image Manipulation Detection using Convolutional Neural Network.
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