Parallel Computer For Face Recognition Using Artificial Intelligence

We implemented a facial recognition application with AI. We used the VGGFace model for our neural net to identify faces. The application includes training and recognizing. The training part is to add new faces to our system, while the recognizing part is to determine the identity of a face. The application runs on multiple cores and able to scale with different numbers of cores. The implementation for parallelism uses tensorflow. For performance measurements, we used the Task Manager application found in Windows with special option known as `affinity to choose the number of cores to run the application. The results show that our system scales in performance with number of processors up to twelve.