A review of machine learning for near-infrared spectroscopy

• المؤلفون الرئيسيون: Zhang, Wenwen, Kasun, Liyanaarachchi Chamara, Wang, Qi Jie, Zheng, Yuanjin, Lin, Zhiping
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Electrical and electronic engineering::Optics, optoelectronics, photonics; Machine Learning; Near-Infrared Spectroscopy; Non-Invasive Measurement; Deep Architectures; Light Absorption
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/167770
• المؤسسة: 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...