Plankton-FL: Exploration of Federated Learning for Privacy-Preserving Training of Deep Neural Networks for Phytoplankton Classification. (arXiv:2212.08990v1 [cs.LG])

Creating high-performance generalizable deep neural networks for
phytoplankton monitoring requires utilizing large-scale data coming from
diverse global water sources. A major challenge to training such networks lies
in data privacy, where data collected at different facilities are often
restricted from being transferred to a centralized location. A promising
approach to overcome this challenge is federated learning, where training is
done at site level on local data, and only the model parameters are exchanged
over the network to generate a global …

classification federated learning networks neural networks privacy training