Artificial intelligence (and related topics, e.g., machine learning, deep learning, artificial neural networks or ANNs) as applied to the teaching and to the practice of analytical spectrochemistry

Celine Tat; Vassili Karanassios

doi:10.1117/12.3013600

7 June 2024 Artificial intelligence (and related topics, e.g., machine learning, deep learning, artificial neural networks or ANNs) as applied to the teaching and to the practice of analytical spectrochemistry

Celine Tat, Vassili Karanassios

Author Affiliations +

Proceedings Volume 13026, Next-Generation Spectroscopic Technologies XVI; 130260H (2024) https://doi.org/10.1117/12.3013600
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

In this paper, the application of Artificial Intelligence (AI) and related topics (e.g., Machine Learning, Artificial Neural Networks (ANNs), deep learning) as they apply to analytic spectrometry (e.g., either using Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES), or a portable, battery-operated microplasma-OES) using a fiber-optic spectrometer) will be described, and the application of AI to teaching analytical atomic spectrometry will be outlined.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Celine Tat and Vassili Karanassios "Artificial intelligence (and related topics, e.g., machine learning, deep learning, artificial neural networks or ANNs) as applied to the teaching and to the practice of analytical spectrochemistry", Proc. SPIE 13026, Next-Generation Spectroscopic Technologies XVI, 130260H (7 June 2024); https://doi.org/10.1117/12.3013600

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