Abstarct: Today, there are numerous systems for face recognition and identification, each of which has been able to partly resolve the demands of users of these systems in a limited data set. On the other hand, augmented reality, as a new technology for showing additional information for detected subjects on camera, has a high potential for attracting the audiences. In this thesis, we proposed a CNN-baxsed face authentication system, combined with augmented reality. An application has been developed to show the information of the faculty members, as an augmented reality, while a face image is detected on camera. To evaluate the proposed method, we prepared a dataset of face images of 100 faculty members. These images are taken from the faculty boards of the Shahrood University of Technology. Since the images are fixed and only the camera position and ambient brightness are changed, we got the outstanding recognition rate of 99.45%. The network response time for each sample, on average, is 47ms, which allows processing of 21 frxames per second (on system with processor: CPU Intel-Core i7 2.8GH GPU AMD M440). For the augmented reality section, when user moves his camera on the image of a faculty member, his face is recognized and the appropriate augmented reality is aligned with the original face direction and shown to the user.