Work

Sensing Anomalies as Potential Hazards: Datasets and Benchmarks

Year: 2022

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-031-15908-4_17

Authors: Dario Mantegazza, Carlos Redondo, Fran Espada, Luca M. Gambardella, Alessandro Giusti, Jérôme Guzzi

Institutions: University of Applied Sciences and Arts of Southern Switzerland, Dalle Molle Institute for Artificial Intelligence Research

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3210801543

FWCI: 0.967

Cites: 41

Cited by: 8

Related to: 10