We investigate deep learning-based regression and classification for quality of transmission estimation in single-mode and few-mode fiber links. Results show efficiency and low complexity in both methods, however, regression performs better and classification is faster.
Deep Learning Regression vs. Classification for QoT Estimation in SMF and FMF Links / Amirabadi, Ma; Kahaei, Mh; Nezamalhosseini, Sa; Carena, A. - ELETTRONICO. - (2022), pp. -3. (Intervento presentato al convegno Italian Conference on Optics and Photonics (ICOP) tenutosi a Trento (Italy) nel 15-17 June 2022) [10.1109/ICOP56156.2022.9911716].
Deep Learning Regression vs. Classification for QoT Estimation in SMF and FMF Links
Amirabadi, MA;Carena, A
2022
Abstract
We investigate deep learning-based regression and classification for quality of transmission estimation in single-mode and few-mode fiber links. Results show efficiency and low complexity in both methods, however, regression performs better and classification is faster.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2984821