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"EFFECT: An End-to-End Framework for Evaluating Strategies for Parallel AI ..."

Matthias Stammler et al. (2023)

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DOI: 10.1016/J.PROCS.2023.08.188

access: open

type: Conference or Workshop Paper

metadata version: 2024-10-06

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  - conf/inns-dlia/StammlerHKSHH023
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  - https://dblp.org/rec/conf/inns-dlia/StammlerHKSHH023
Matthias Stammler, Julian Höfer, David Kraus, Patrick Schmidt, Tim Hotfilter, Tanja Harbaum, Jürgen Becker:
EFFECT: An End-to-End Framework for Evaluating Strategies for Parallel AI Anomaly Detection. INNS DLIA@IJCNN 2023: 499-508

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