Research on Face Recognition Algorithm Based on TensorFlow Framework

With the breakthrough of deep learning technology, especially the development of models such as Generative Adversarial Networks (GANs), Artificial Intelligence (AI) can generate highly realistic images. More and more research institutions and enterprises are investing in the field of AI generation. However, the wide application of AI-generated images has also brought many potential risks. This paper intends to build a CNN convolutional neural network model based on the TensorFlow framework to design a face recognition algorithm to identify real images and AI-generated images. First, a large number of real face and AI-synthesized face image datasets for model training are collected; after image processing, a CNN model is built; the processed images are input to the built CNN model, which extracts features and trains the images; finally, the recognition results are verified, and the algorithm is optimized and improved according to the accuracy of the identification results.