├── Project Presentation.pdf ├── Project Proposal Presentation.pdf ├── Project Proposal.pdf ├── Project Report.pdf ├── Project.ipynb └── README.md /Project Presentation.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/parth2608/Deepfakes-Detection/3815589481dbb91f732a94c7ddc7cc6a171a76c3/Project Presentation.pdf -------------------------------------------------------------------------------- /Project Proposal Presentation.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/parth2608/Deepfakes-Detection/3815589481dbb91f732a94c7ddc7cc6a171a76c3/Project Proposal Presentation.pdf -------------------------------------------------------------------------------- /Project Proposal.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/parth2608/Deepfakes-Detection/3815589481dbb91f732a94c7ddc7cc6a171a76c3/Project Proposal.pdf -------------------------------------------------------------------------------- /Project Report.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/parth2608/Deepfakes-Detection/3815589481dbb91f732a94c7ddc7cc6a171a76c3/Project Report.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Deepfakes-Detection 2 | 3 | Designed and implemented a custom CNN learning architecture for deep fake image detection using a pre-trained Xception model and achieved 82.66% accuracy on a diverse dataset 4 | --------------------------------------------------------------------------------