Cargando…
Autoencoder-based Online Data Quality Monitoring for the CMS Electromagnetic Calorimeter
The online Data Quality Monitoring system (DQM) of the CMS electromagnetic calorimeter (ECAL) is a crucial operational tool that allows ECAL experts to quickly identify, localize, and diagnose a broad range of detector issues that would otherwise hinder physics-quality data taking. Although the exis...
Autores principales: | Harilal, Abhirami, Park, Kyungmin, Andrews, Michael, Paulini, Manfred |
---|---|
Lenguaje: | eng |
Publicado: |
2023
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2869198 |
Ejemplares similares
-
Autoencoder-based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter
por: Abadjiev, D., et al.
Publicado: (2023) -
Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier
por: Grönroos, Sonja, et al.
Publicado: (2023) -
Lorentz Group Equivariant Autoencoders
por: Hao, Zichun, et al.
Publicado: (2022) -
CALICE Si/W electromagnetic Calorimeter
por: Reinhard, Marcel
Publicado: (2009) -
Anomaly Detection With Conditional Variational Autoencoders
por: Pol, Adrian Alan, et al.
Publicado: (2020)