A research team led by Prof. Gao Xiaoming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has improved residual neural networks to accurately classify and identify microplastics using low-quality Raman spectra, even under non-ideal experimental conditions.

“It detects and classifies microplastics when the data is cluttered with noise,” said Prof. Gao, “and it does this without overloading computing power.”

The research results are published in Talanta.