Enhanced Forgery Detection of Fake Face in Forensic Investigation using Convolution Neural Network

The proliferation of image editing tools has led to a surge in forged images, making it imperative to develop effective detection methods. This survey explores the application of deep learning, specifically the Convolutional Neural Network (CNN) RESNET50 algorithm for forged image detection in the field of forensic investigation. By analyzing various existing advancded techniques, CNNs have demonstrated their effectiveness in classifying fake faces in forensic investigations. The survey highlights the performance advantages of CNNs when trained on extensive datasets. This research study provides insights into future research directions and potential improvements in forged image detection. It emphasizes the need for building larger and more diverse datasets to facilitate comparison and evaluation of different detection methods.