Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning

Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning

Laser-induced breakdown spectroscopy is a versatile technique that can be used to quickly measure the concentration of elements in ambient air. We tackle the issues of performance and trustworthiness of the statistical model used for predictions. We propose a method for improving the performance and...

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Bibliographic Details
Main Authors: Finotello Riccardo, L’Hermite Daniel, Quéré Celine, Rouge Benjamin, Tamaazousti Mohamed, Sirven Jean-Baptiste
Format: Article
Language:English
Published: EDP Sciences 2023-01-01
Series:EPJ Web of Conferences
Subjects:
libs
trustworthy ai
simulation
multitask
neural networks
Online Access:https://www.epj-conferences.org/articles/epjconf/pdf/2023/14/epjconf_animma2023_01005.pdf

Internet

https://www.epj-conferences.org/articles/epjconf/pdf/2023/14/epjconf_animma2023_01005.pdf

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