Detection of tampered real time videos using deep neural networks

HIGHLIGHTS

  • What: Finding the temporal and spatial extent of copy-move manipulation is the primary goal of copy move video forgery detection systems. Based on the review process the proposed system used a pre-trained VGG16 model along with customized Convolution Neural_Network is used for the classification of proposed video forgery detection.
  • Who: Posted Date June and collaborators from the Sathyabama Institute of Science and Technology have published the paper: Detection of Tampered Real Time Videos Using Deep Neural Networks, in the Journal: (JOURNAL)
  • How: The confusion matrix of the custom CNN model on . . .

     

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