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Releases: kubeedge/sedna

Sedna v0.1.0 release

01 Apr 12:19
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Incremental Learning

  • Support Automatically retraining, evaluating, and updating models based on the data generated at the edge.
  • Support time trigger, sample size trigger, and precision-based trigger.
  • Support hard sample discovering of unlabeled data, for reducing the manual labeling workload.

Federated Learning

  • Support automatic deployment of federated learning training scripts to the edge.
  • Support user-defined aggregation algorithms.
  • Integrate the FedAvg algorithm.

Joint Inference

  • Supports automatic deployment of big model and little model to cloud and edge.
  • Supports discovering hard examples and sending them to the cloud to improve the overall inference accuracy.

Published images

The published images can be found under docker.io/kubeedge:
kubeedge/sedna-gm:v0.1.0
kubeedge/sedna-lc:v0.1.0
kubeedge/sedna-example-joint-inference-helmet-detection-big:v0.1.0
kubeedge/sedna-example-joint-inference-helmet-detection-little:v0.1.0
kubeedge/sedna-example-incremental-learning-helmet-detection:v0.1.0
kubeedge/sedna-example-federated-learning-surface-defect-detection-train:v0.1.0
kubeedge/sedna-example-federated-learning-surface-defect-detection-aggregation:v0.1.0