When dealing with sensor's data, it's important to keep track of what it's really happening in the tracked environments since failures, interruptions and misreadings must be expected at any time. Especially with logging processes involving extremely voluminous reports, an automatic method to detect entries that are not following the normal distribution of data (i.e. anomalies) should be the ideal solution. In the presented work the task performed by the autoencoder is to generate a reproduction error, used as metric for the classification of a sample in one of two classes: anomalous or non-anomalous.

A Customized Approach to Anomalies Detection by using Autoencoders / Aureli, R.; Brandizzi, N.; De Magistris, G.; Brociek, R.. - 3092:(2021), pp. 53-59. (Intervento presentato al convegno 2021 Scholar's Yearly Symposium of Technology, Engineering and Mathematics, SYSTEM 2021 tenutosi a Catania; Italia).

A Customized Approach to Anomalies Detection by using Autoencoders

Brandizzi N.
Co-primo
Data Curation
;
De Magistris G.
Co-primo
Investigation
;
2021

Abstract

When dealing with sensor's data, it's important to keep track of what it's really happening in the tracked environments since failures, interruptions and misreadings must be expected at any time. Especially with logging processes involving extremely voluminous reports, an automatic method to detect entries that are not following the normal distribution of data (i.e. anomalies) should be the ideal solution. In the presented work the task performed by the autoencoder is to generate a reproduction error, used as metric for the classification of a sample in one of two classes: anomalous or non-anomalous.
2021
2021 Scholar's Yearly Symposium of Technology, Engineering and Mathematics, SYSTEM 2021
ASIC; FPGA; Parallel dsp; Ti-adc
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A Customized Approach to Anomalies Detection by using Autoencoders / Aureli, R.; Brandizzi, N.; De Magistris, G.; Brociek, R.. - 3092:(2021), pp. 53-59. (Intervento presentato al convegno 2021 Scholar's Yearly Symposium of Technology, Engineering and Mathematics, SYSTEM 2021 tenutosi a Catania; Italia).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1625561
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