Identification of Polymers with a Small Data Set of Mid-infrared Spectra: A Comparison between Machine Learning and Deep Learning Models-Reference-Cited by-同舟云学术

Identification of Polymers with a Small Data Set of Mid-infrared Spectra: A Comparison between Machine Learning and Deep Learning Models

Published:2023-01-11 Issue:11 Volume:10 Page:1030-1035
ISSN:2328-8930
Container-title:Environmental Science & Technology Letters
language:en
Short-container-title:Environ. Sci. Technol. Lett.

Author:

Tian Xin¹^ORCID,Beén Frederic¹²^ORCID,Sun Yiqun³⁴,van Thienen Peter¹,Bäuerlein Patrick S.¹^ORCID

Affiliation:

1. KWR Water Research Institute, Groningenhaven 7, 3433 PENieuwegein, The Netherlands

2. Chemistry for Environment & Health, Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands

3. School of Earth Sciences and Engineering, Hohai University, Nanjing210098, China

4. College of Hydrology and Water Resources, Hohai University, Nanjing210098, China

Funder

Dutch and Flemish water utilities

Publisher

American Chemical Society (ACS)

Subject

Health, Toxicology and Mutagenesis,Pollution,Waste Management and Disposal,Water Science and Technology,Ecology,Environmental Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.estlett.2c00949

Reference41 articles.

1. Addressing the environmental and health impacts of microplastics requires open collaboration between diverse sectors

2. Rapid Identification and Quantification of Microplastics in the Environment by Quantum Cascade Laser-Based Hyperspectral Infrared Chemical Imaging

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4. Determination of the microplastics emission in the effluent of a municipal waste water treatment plant using Raman microspectroscopy

5. Analysis of microplastics in drinking water and other clean water samples with micro-Raman and micro-infrared spectroscopy: minimum requirements and best practice guidelines

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