Work

AutoAD: an Automated Framework for Unsupervised Anomaly Detection

Year: 2022

Type: conference-paper

Source: IEEE International Conference on Data Science and Advanced Analytics (DSAA)

DOI: 10.1109/dsaa54385.2022.10032396

Authors: Andrian Putina, Maroua Bahri, Flavia Salutari, Mauro Sozio

Institutions: Institut Polytechnique de Paris, Laboratoire Traitement et Communication de l’Information, Institut national de recherche en sciences et technologies du numérique, MIMOVE: Middleware on the Move

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4304940689

FWCI: 1.097

Cites: 22

Cited by: 8

Related to: 10