Marco Seeland

According to our database, Marco Seeland authored at least 9 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks.

Daniel Scheliga, Patrick Mäder, Marco Seeland

CoRR, 2023

Dropout Is NOT All You Need to Prevent Gradient Leakage.

Daniel Scheliga, Patrick Maeder, Marco Seeland

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Combining Variational Modeling with Partial Gradient Perturbation to Prevent Deep Gradient Leakage.

Daniel Scheliga, Patrick Mäder, Marco Seeland

CoRR, 2022

PRECODE - A Generic Model Extension to Prevent Deep Gradient Leakage.

Daniel Scheliga, Patrick Mäder, Marco Seeland

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

2020

Flora Capture: a citizen science application for collecting structured plant observations.

David Boho, Michael Rzanny, Jana Wäldchen, Fabian Nitsche, Alice Deggelmann, Hans Christian Wittich, Marco Seeland, Patrick Mäder

BMC Bioinform., 2020

2019

Efficiently Annotating Object Images with Absolute Size Information Using Mobile Devices.

Martin Hofmann, Marco Seeland, Patrick Mäder

Int. J. Comput. Vis., 2019

Image-based classification of plant genus and family for trained and untrained plant species.

Marco Seeland, Michael Rzanny, David Boho, Jana Wäldchen, Patrick Mäder

BMC Bioinform., 2019

2018

Automated plant species identification - Trends and future directions.

Jana Wäldchen, Michael Rzanny, Marco Seeland, Patrick Mäder

PLoS Comput. Biol., 2018

Recommending plant taxa for supporting on-site species identification.

Hans Christian Wittich, Marco Seeland, Jana Wäldchen, Michael Rzanny, Patrick Mäder

BMC Bioinform., 2018