A review of machine learning for near-infrared spectroscopy

• Main Authors: Zhang, Wenwen, Kasun, Liyanaarachchi Chamara, Wang, Qi Jie, Zheng, Yuanjin, Lin, Zhiping
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Electrical and electronic engineering::Optics, optoelectronics, photonics; Machine Learning; Near-Infrared Spectroscopy; Non-Invasive Measurement; Deep Architectures; Light Absorption
• Online Access: https://hdl.handle.net/10356/167770
• Institution: Nanyang Technological University

The analysis of infrared spectroscopy of substances is a non-invasive measurement tech nique that can be used in analytics. Although the main objective of this study is to provide a review of machine learning (ML) algorithms that have been reported for analyzing near-infrared (NIR) spectroscopy fr...