Marco Seeland - RankMe

18 papers A* 1A 1Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Brood Cell Detection in Layer Trap Nests for Bees and Wasps: Balancing Labeling Effort and Species Coverage. CoRR Chenchang Liu, Felix Fornoff, Annika Grasreiner, Patrick Maeder, Henri Greil, Marco Seeland
2026	J	`jnl`	Lowering barriers to federated learning: collaboration management and provenance. J. Big Data Marius Schlegel, Daniel Scheliga, Kai-Uwe Sattler, Marco Seeland, Patrick Mäder
2026	J	`jnl`	Model utility and explainability in federated learning - A case study in healthcare using fundus oculi datasets. J. Biomed. Informatics Niklas Penzel, Daniel Scheliga, Hannes Oppermann, Patrick Mäder, Jens Haueisen, Joachim Denzler, Marco Seeland
2026	—	`conf`	Order-Level Arthropod Detection Using Deep Learning: Addressing Scale Variability through Synthetic Data. VISAPP (2) Chenchang Liu, Svetlana Ionova, Patrick Mäder, Marco Seeland
2025	J	`jnl`	Privacy preserving federated learning with convolutional variational bottlenecks. Cybersecur. Daniel Scheliga, Patrick Mäder, Marco Seeland
2024	—	`conf`	Collaboration Management for Federated Learning. ICDEW Marius Schlegel, Daniel Scheliga, Kai-Uwe Sattler, Marco Seeland, Patrick Mäder
2024	J	`jnl`	Feature-Based Dataset Fingerprinting for Clustered Federated Learning on Medical Image Data. Appl. Artif. Intell. Daniel Scheliga, Patrick Mäder, Marco Seeland
2023	A*	`conf`	Dropout Is NOT All You Need to Prevent Gradient Leakage. AAAI Daniel Scheliga, Patrick Maeder, Marco Seeland
2023	J	`jnl`	Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks. CoRR Daniel Scheliga, Patrick Mäder, Marco Seeland
2022	J	`jnl`	Combining Variational Modeling with Partial Gradient Perturbation to Prevent Deep Gradient Leakage. CoRR Daniel Scheliga, Patrick Mäder, Marco Seeland
2022	J	`jnl`	Dropout is NOT All You Need to Prevent Gradient Leakage. CoRR Daniel Scheliga, Patrick Mäder, Marco Seeland
2022	A	`conf`	PRECODE - A Generic Model Extension to Prevent Deep Gradient Leakage. WACV Daniel Scheliga, Patrick Mäder, Marco Seeland
2021	J	`jnl`	PRECODE - A Generic Model Extension to Prevent Deep Gradient Leakage. CoRR Daniel Scheliga, Patrick Mäder, Marco Seeland
2020	J	`jnl`	Flora Capture: a citizen science application for collecting structured plant observations. BMC Bioinform. David Boho, Michael Rzanny, Jana Wäldchen, Fabian Nitsche, Alice Deggelmann, Hans Christian Wittich, Marco Seeland, Patrick Mäder
2019	J	`jnl`	Efficiently Annotating Object Images with Absolute Size Information Using Mobile Devices. Int. J. Comput. Vis. Martin Hofmann, Marco Seeland, Patrick Mäder
2019	J	`jnl`	Image-based classification of plant genus and family for trained and untrained plant species. BMC Bioinform. Marco Seeland, Michael Rzanny, David Boho, Jana Wäldchen, Patrick Mäder
2018	J	`jnl`	Automated plant species identification - Trends and future directions. PLoS Comput. Biol. Jana Wäldchen, Michael Rzanny, Marco Seeland, Patrick Mäder
2018	J	`jnl`	Recommending plant taxa for supporting on-site species identification. BMC Bioinform. Hans Christian Wittich, Marco Seeland, Jana Wäldchen, Michael Rzanny, Patrick Mäder