Work

Interpretable Data-Driven Anomaly Detection in Industrial Processes with ExIFFI

Year: 2024

Type: conference-paper

Source: IEEE Forum on Research and Technologies for Society and Industry Innovation (RTSI)

DOI: 10.1109/rtsi61910.2024.10761374

Authors: Davide Frizzo, Francesco Borsatti, Alessio Arcudi, Antonio De Moliner, Roberto Oboe, Gian Antonio Susto

Institution: University of Padua

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4404740359

FWCI: 0.294

Cites: 14

Cited by: 1

Related to: 10