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Matthias Boljen / DYNA Tools
MIT LicenseCollection of scripts to manipulate LS-DYNA keyfiles
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DataSov / ekep
Apache License 2.0ProVerif formal models for the (modified) EKEP attestation protocol. Forked from https://github.com/google/ekep-analysis/.
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elena-ns3-lte / elena
GNU General Public License v2.0 or laterUpdated -
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Modbus communication for the "hydrogen battery" in the context of the project "Energiepuffer".
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ezCar2X / ezCar2X
MIT LicenseRapid-prototyping framework for connected vehicle protocols and applications
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Federated learning (FL) enables multiple devices to collaboratively train a global model while maintaining data on local servers. Each device trains the model on its local server and shares only the model updates (i.e., gradient weights) during the aggregation step. A significant challenge in FL is managing the feature distribution of novel, unbalanced data across devices. In this paper, we propose an FL approach using few-shot learning and aggregation of the model weights on a global server. We introduce a dynamic early stopping method to balance out-of-distribution classes based on representation learning, specifically utilizing the maximum mean discrepancy of feature embeddings between local and global models. An exemplary application of FL is orchestrating machine learning models along highways for interference classification based on snapshots from global navigation satellite system (GNSS) receivers. Extensive experiments on four GNSS datasets from two real-world highways and controlled environments demonstrate that our FL method surpasses state-of-the-art techniques in adapting to both novel interference classes and multipath scenarios.
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PHTDev / harbor
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Florian Schiffel / ICV-mmdetection_baseCode
Apache License 2.0Updated