Findings on Machine Learning Discussed by Investigators at Sapienza University of Rome (A Systematic Approach To Develop Safety-related Undesired Event Databases for Machine Learning Analyses: Application To Confined Space Incidents)

Robotics & Machine Learning Daily News2024，Issue(Feb.15) ：72-72.DOI:10.1016/j.psep.2023.11.046

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NETL
NSTL
Elsevier

Findings on Machine Learning Discussed by Investigators at Sapienza University of Rome (A Systematic Approach To Develop Safety-related Undesired Event Databases for Machine Learning Analyses: Application To Confined Space Incidents)

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Abstract

Investigators publish new report on Machine Learning. According to news reporting originating in Rome, Italy, by NewsRx journalists, research stated, “In Occupational Safety and Health (OSH) and operational safety, confined spaces are high-risk working areas, where frequent serious and fatal incidents occur. However, there is a limited use of data-driven approaches based on Machine Learning (ML) techniques for learning from such incidents.”

Key words

Rome/Italy/Europe/Cyborgs/Emerging Technologies/Machine Learning/Sapienza University of Rome

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出版年

2024

Robotics & Machine Learning Daily News

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