Unmasking Deep Fake Images with Intelligent Detection

This is a project that deals with the rising threat of deepfake technology, which manipulates media to create very realistic yet misleading content. In the fight against this, we propose a comprehensive deepfake detection system capable of analyzing images. For image analysis, we utilize Convolutional Neural Networks, which are specifically VGG16 and MobileNet, to extract relevant features and classify images as authentic or manipulated. We come up with the development of the web application where it eases the process through the use of uploading the images to be used in analyzing where the real time accurate results regarding classification is available to the users. Last, the system will optimize performance purposes as well. The combination of these techniques will make our system significantly contribute to the detection and mitigation of deepfake content in digital media, empowering users to identify manipulated images and safeguard the integrity of visual information across various platforms.