Augmentation assisted robust fringe detection on unseen experimental signals applied to optical feedback interferometry using a deep network Article Swipe
Related Concepts
Generalization
Computer science
Artificial intelligence
Domain (mathematical analysis)
Interferometry
Artificial neural network
Deep neural networks
SIGNAL (programming language)
Computer vision
Pattern recognition (psychology)
Mathematics
Optics
Physics
Programming language
Mathematical analysis
Sumair Saeed Khurshid
,
Wajahat Hussain
,
Usman Zabit
,
Olivier D. Bernal
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.36227/techrxiv.21303804.v3
· OA: W4327948912
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.36227/techrxiv.21303804.v3
· OA: W4327948912
<p>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.</p>
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