Augmentation assisted robust fringe detection on unseen experimental signals applied to optical feedback interferometry using a deep network

In this work, we propose using deep neural 2D networks, which have renowned generalization performance on unseen data. It specifically explains the use of Novel Augmentation technique for SMI Fringe detection and classification. Overall, it highlights the importance of data augmentation in computer vision algorithms. The results prove that computer vision can be used to cater the problems in signal processing and photoelectronics domain.