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Machine Learning Techniques for THz Imaging and Time-Domain Spectroscopy

Authors :
Hochong Park
Joo-Hiuk Son
Source :
Sensors (Basel, Switzerland), Sensors, Vol 21, Iss 1186, p 1186 (2021)
Publication Year :
2020

Abstract

Terahertz imaging and time-domain spectroscopy have been widely used to characterize the properties of test samples in various biomedical and engineering fields. Many of these tasks require the analysis of acquired terahertz signals to extract embedded information, which can be achieved using machine learning. Recently, machine learning techniques have developed rapidly, and many new learning models and learning algorithms have been investigated. Therefore, combined with state-of-the-art machine learning techniques, terahertz applications can be performed with high performance that cannot be achieved using modeling techniques that precede the machine learning era. In this review, we introduce the concept of machine learning and basic machine learning techniques and examine the methods for performance evaluation. We then summarize representative examples of terahertz imaging and time-domain spectroscopy that are conducted using machine learning.

Details

ISSN :
14248220
Volume :
21
Issue :
4
Database :
OpenAIRE
Journal :
Sensors (Basel, Switzerland)
Accession number :
edsair.doi.dedup.....70791f89cb4bee078666ac8b12a9e9dc