activity
20182022
most citedMachine Learning-based Anomaly Detection in Optical Fiber Monitoring

135 citations · 519 across the 30 of their papers we have counts for

collaborators

31 papers

cs.LG202211 cited

Degradation Prediction of Semiconductor Lasers using Conditional Variational Autoencoder

Khouloud Abdelli, Helmut Griesser, Christian Neumeyr +2

Semiconductor lasers have been rapidly evolving to meet the demands of next-generation optical networks. This imposes much more stringent requirements on the laser reliability, whi…

cs.LG202225 cited

A Machine Learning-based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication

Khouloud Abdelli, Helmut Griesser, Stephan Pachnicke

Semiconductor lasers, one of the key components for optical communication systems, have been rapidly evolving to meet the requirements of next generation optical networks with resp…

cs.NI2022135 cited

Machine Learning-based Anomaly Detection in Optical Fiber Monitoring

Khouloud Abdelli, Joo Yeon Cho, Florian Azendorf +3

Secure and reliable data communication in optical networks is critical for high-speed Internet. However, optical fibers, serving as the data transmission medium providing connectiv…

cs.NI202250 cited

Reflective Fiber Faults Detection and Characterization Using Long-Short-Term Memory

Khouloud Abdelli, Helmut Griesser, Peter Ehrle +2

To reduce operation-and-maintenance expenses (OPEX) and to ensure optical network survivability, optical network operators need to detect and diagnose faults in a timely manner and…

eess.SP20221 cited

Convolutional Neural Networks for Reflective Event Detection and Characterization in Fiber Optical Links Given Noisy OTDR Signals

Khouloud Abdelli, Helmut Griesser, Stephan Pachnicke

Fast and accurate fault detection and localization in fiber optic cables is extremely important to ensure the optical network survivability and reliability. Hence there exists a cr…

eess.SP202210 cited

Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques

Khouloud Abdelli, Danish Rafique, Helmut Griesser +1

A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 um InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime…