Research on Deep Forged Image Detection Based on Deep Learning Fusion of Multidimensional Recognition Features

This study relies on deep learning to develop a deep forgery image detection model that integrates multidimensional recognition features. The use of deep learning techniques to extract and explore visual and semantic features of forged images covers a comprehensive coverage from pixel level distribution, texture construction to high-order semantic content. By designing a feature fusion mechanism that integrates multiple recognition features into the detection algorithm, the accuracy and stability of the detection are enhanced. Tests on multiple fake image detection standard datasets have shown excellent monitoring capabilities, strong practical potential, and broad application prospects. The research has opened up new technological means for deep forgery technology, which plays an important role in ensuring the authenticity of images and maintaining information security.