In recent years, with the increasing demand for intelligent society, intelligent photonics has
developed rapidly. Machine learning (ML), as a subset of artificial intelligence (AI), has …

Multimode fiber (MMF) sensors have been extensively developed and utilized in various
sensing applications for decades. Traditionally, the performance of MMF sensors was …

Machine Learning for Future Fiber-Optic Communication Systems provides a
comprehensive and in-depth treatment of machine learning concepts and techniques …

Over the last three decades, fiber optic sensors (FOS) have gained a lot of attention for their
wide range of monitoring applications across many industries, including aerospace …

Machine learning (ML) has achieved phenomenal success in revolutionizing a number of
science and engineering disciplines over the last decade. Naturally, it is also being …

The mutual constraint between sensitivity and measurement range has always been a
problem that restricts the development and application of optical fiber interference sensors …

Multimode fiber (MMF) specklegram sensors have recently drawn significant attention due to
the incorporation of machine learning (ML) algorithms in detecting different sensing …

Fiber Specklegram Sensors (FSSs) are highly sensitive to external perturbations, however,
trying to locate perturbation's position remains as a barely addressed study. In this work, a …

The spectral response produced when a high-sensitivity optical fiber sensor (OFS) is subject
to an external perturbation has recently been shown to contain rich information that can be …

Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …