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Gianluca Setti

3 accepted papers

2023

Second-Order Statistic Deviation to Model Anomalies in the Design of Unsupervised Detectors

ICASSP 2023accepted

Anomaly Detection is a challenging task due to the limited knowledge about possible anomalies. This issue can be tackled by modeling anomalies through domain expertise or collecting sufficient anomalous data. However, some domains, such as monitoring systems, require detectors that are capable of de…

Cited by 0SourceScholar
2019

Chained Compressed Sensing for Iot Node Security

ICASSP 2019accepted

Compressed sensing can be used to yield both compression and a limited form of security to the readings of sensors. This can be most useful when designing the low-resources sensor nodes that are the backbone of IoT applications. Here, we propose to use chaining of subsequent plaintexts to improve th…

Cited by 0SourceScholar
2015

Average recovery performances of non-perfectly informed compressed sensing: With applications to multiclass encryption

ICASSP 2015accepted

The sensitivity of recovery algorithms with respect to a perfect knowledge of the encoding matrix is a general issue in many application scenarios in which compressed sensing is an option to acquire or encode natural signals. Quantifying this sensitivity in order to predict the result of signal reco…

Cited by 0SourceScholar