Search Results for author:
Found 3 papers, 0 papers with code
Plankton-FL: Exploration of Federated Learning for Privacy-Preserving Training of Deep Neural Networks for Phytoplankton Classification
In this study, we explore the feasibility of leveraging federated learning for privacy-preserving training of deep neural networks for phytoplankton classification.
Towards Generating Large Synthetic Phytoplankton Datasets for Efficient Monitoring of Harmful Algal Blooms
Thus, this work demonstrates the ability of GANs to create large synthetic datasets of phytoplankton from small training datasets, accomplishing a key step towards sustainable systematic monitoring of harmful algal blooms.
Numerical Demultiplexing of Color Image Sensor Measurements via Non-linear Random Forest Modeling
A numerical demultiplexer is then learned via non-linear random forest modeling based on the forward model.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
