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International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
3463, Volume 7, PP. 25-30, [9] Usha Kosarkar, Prachi Sasankar(2021), “ A study for
https://doi.org/10.46335/IJIES.2022.7.8.5 Face Recognition using techniques PCA and KNN”,
[6] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2022), Journal of Computer Engineering (IOSR-JCE), 2278-
“Revealing and Classification of Deepfakes Videos 0661,PP 2-5,
Images using a Customize Convolution Neural [10] Usha Kosarkar, Gopal Sakarkar (2024), “Design an
Network Model”, International Conference on Machine efficient VARMA LSTM GRU model for identification of
Learning and Data Engineering (ICMLDE), 7 & 8 deep-fake images via dynamic window-based spatio-
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September 2022, 2636-2652, Volume 218, PP. 2636- temporal analysis”, Journal of Multimedia Tools and
2652, https://doi.org/10.1016/j.procs.2023.01.237 Applications, 1380-7501,
[7] Usha Kosarkar, Gopal Sakarkar (2023), “Unmasking https://doi.org/10.1007/s11042-024-19220-w
Deep Fakes: Advancements, Challenges, and Ethical [11] Usha Kosarkar, Dipali Bhende, “Employing Artificial
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Considerations”, 4 International Conference on Intelligence Techniques in Mental Health Diagnostic
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Electrical and Electronics Engineering (ICEEE),19 & Expert System”, International Journal of Computer
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20 August 2023, 978-981-99-8661-3, Volume 1115, Engineering (IOSR-JCE),2278-0661, PP-40-45,
PP. 249-262, https://doi.org/10.1007/978-981-99- https://www.iosrjournals.org/iosr-
8661-3_19 jce/papers/conf.15013/Volume%202/9.%2040-
[8] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2021), 45.pdf?id=7557
“Deepfakes, a threat to society”, International Journal [12] Usha Kosarkar, Gopal Sakarkar & Mahesh Naik, “A
of Scientific Research in Science and Technology Hybrid Deep Learning Model for robust deep fake
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(IJSRST), 13 October 2021, 2395-602X, Volume 9, detection”, 2 International Conference on Advanced
nd
Issue 6, PP. 1132-1140, Communications and Machine Intelligence (MICA
https://ijsrst.com/IJSRST219682 2023), https://doi.org/10.1007/978-981-97-6222-
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