Harnessing AI for Robust Deep Fake Detection in Image

In the realm of modern computer vision, the emergence of powerful tools has enabled the creation of increasingly convincing deepfake content. Leveraging the capabilities of Generative Adversarial Networks, these advanced techniques manipulate various forms of media, including images, audio, and videos, flawlessly blending them into different contexts. Consequently, Deepfake technology poses a significant threat to the authenticity and trustworthiness of visual content on the internet. The deep learning-based method for deepfake detection is presented in this project. In order to identify trends and anomalies linked to modified content, we train a neural network on a dataset of actual and deepfake images. Our model provides a reliable and efficient method for detecting deepfakes by utilizing the capabilities of deep neural networks to automatically extract pertinent characteristics and generate precise predictions.