VOC-Net: A Deep Learning Model for the Automated Classification of Rotational THz Spectra of Volatile Organic Compounds
Conventional black box machine learning (ML) algorithms for gas-phase species identification from THz frequency region absorption spectra have been reported in the literature. While the robust classification performance of such ML models is promising, the black box nature of these ML tools limits th...
Main Authors: | M. Arshad Zahangir Chowdhury, Timothy E. Rice, Matthew A. Oehlschlaeger |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-08-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/17/8447 |
Similar Items
-
THz Systems Exploiting Photonics and Communications Technologies
by: Jan C. Balzer, et al.
Published: (2023-01-01) -
Terahertz-Wave Absorption Gas Sensing for Dimethyl Sulfoxide
by: Alec Passarelli, et al.
Published: (2022-06-01) -
Research Advances in Allelopathy of Volatile Organic Compounds (VOCs) of Plants
by: Yiqi Xie, et al.
Published: (2021-09-01) -
Determination of the fine structure of a halide perovskite using THz spectroscopy
by: Zhang, Feng, et al.
Published: (2020) -
THz Spectroscopy as a Versatile Tool for Filler Distribution Diagnostics in Polymer Nanocomposites
by: Gleb Gorokhov, et al.
Published: (2020-12-01)