Triggerless data acquisition pipeline for Machine Learning based statistical anomaly detection

This work describes an online processing pipeline designed to identify anomalies in a continuous stream of data collected without external triggers from a particle detector. The processing pipeline begins with a local reconstruction algorithm, employing neural networks on an FPGA as its first stage....

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Bibliographic Details
Main Authors: Grosso Gaia, Lai Nicolò, Migliorini Matteo, Pazzini Jacopo, Triossi Andrea, Zanetti Marco, Zucchetta Alberto
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:EPJ Web of Conferences
Online Access:https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_02033.pdf