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@article{152145,
        author = {Smitha P and Varun Srinivas Naik  and Deepika R and Chaithra K M and B G Sumith Kumar},
        title = {Fake image and video detection using capsule network},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {2},
        pages = {639-642},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152145},
        abstract = {Attackers can now easily manufacture forged photos and movies thanks to recent developments in media generating algorithms. The development of a forged version of a single film collected from a social network can be done in real time using state-of-the-art technology. Although several methods for identifying faked photos and videos have been developed, they are often aimed at specific areas and quickly become obsolete as new types of attacks emerge. The method shown in this project use a capsule network to detect various types of spoofs, ranging from replay attacks utilizing printed images or recorded films to deep convolutional neural networks-based computer-generated videos. It broadens the scope of capsule networks' application beyond their original goal of tackling inverse graphics difficulties},
        keywords = {forged, state-of-the-art, capsule network, spoofs, convolutional neural network},
        month = {},
        }