"Federated Learning for Anomaly Detection in Industrial IoT-enabled ..."

Bohdan Shubyn et al. (2022)

> Home

Details and statistics

DOI: 10.1007/978-3-031-08760-8_35

access: closed

type: Conference or Workshop Paper

metadata version: 2022-06-28

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/iccS/ShubynMMSKGB22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/iccS/ShubynMMSKGB22
Bohdan Shubyn, Dariusz Mrozek, Taras Maksymyuk, Vaidy S. Sunderam, Daniel Kostrzewa, Piotr Grzesik, Pawel Benecki:
Federated Learning for Anomaly Detection in Industrial IoT-enabled Production Environment Supported by Autonomous Guided Vehicles. ICCS (4) 2022: 409-421

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.