A survey on semi-, self-and unsupervised learning for image classification L Schmarje, M Santarossa, SM Schröder, R Koch IEEE Access 9, 82146-82168, 2021 | 258 | 2021 |
Machine learning techniques to characterize functional traits of plankton from image data EC Orenstein, SD Ayata, F Maps, ÉC Becker, F Benedetti, T Biard, ... Limnology and oceanography 67 (8), 1647-1669, 2022 | 80 | 2022 |
MorphoCluster: efficient annotation of plankton images by clustering SM Schröder, R Kiko, R Koch Sensors 20 (11), 3060, 2020 | 68 | 2020 |
Particulate matter flux interception in oceanic mesoscale eddies by the polychaete Poeobius sp. S Christiansen, HJ Hoving, F Schütte, H Hauss, J Karstensen, ... Limnology and Oceanography 63 (5), 2093-2109, 2018 | 60 | 2018 |
Fuzzy overclustering: Semi-supervised classification of fuzzy labels with overclustering and inverse cross-entropy L Schmarje, J Brünger, M Santarossa, SM Schröder, R Kiko, R Koch Sensors 21 (19), 6661, 2021 | 35 | 2021 |
A data-centric approach for improving ambiguous labels with combined semi-supervised classification and clustering L Schmarje, M Santarossa, SM Schröder, C Zelenka, R Kiko, J Stracke, ... European Conference on Computer Vision, 363-380, 2022 | 21 | 2022 |
Low-shot learning of plankton categories SM Schröder, R Kiko, JO Irisson, R Koch German Conference on Pattern Recognition, 391-404, 2018 | 17 | 2018 |
Assessing Representation Learning and Clustering Algorithms for Computer-Assisted Image Annotation—Simulating and Benchmarking MorphoCluster SM Schröder, R Kiko Sensors 22 (7), 2775, 2022 | 3 | 2022 |
PlanktonID–Combining deep learning, in situ imaging and citizen science to resolve the distribution of zooplanktonin major upwelling regions R Kiko, S Christiansen, SM Schröder, R Koch, L Stemmann ICEI 2018: 10th International Conference on Ecological Informatics …, 2018 | 2 | 2018 |
S2C2-An orthogonal method for Semi-Supervised Learning on ambiguous labels L Schmarje, M Santarossa, SM Schröder, C Zelenka, R Kiko, J Stracke, ... | 1 | 2021 |
Image Inpainting with GANs on LOKI Dataset RC Binici, A Onan, R Koch, SM Schröder 2024 Innovations in Intelligent Systems and Applications Conference (ASYU), 1-6, 2024 | | 2024 |
Large-scale patterns of marine snow in the Southern Ocean and the impact of fronts S O'Daly, G Hennon, TB Kelly, R Kiko, RM Lekanoff, J Pretty, SM Schröder, ... 2024 Ocean Sciences Meeting, 2024 | | 2024 |
Supplemental Information: Machine learning techniques to characterize functional traits of plankton from image data EC Orenstein, SD Ayata, F Maps, ÉC Becker, F Benedetti, T Biard, ... Association for the Sciences of Limnology and Oceanography, 2022 | | 2022 |
EcoTaxa: A human-computer interface to classify images along a taxonomy with the help of machine-learning JO Irisson, SM Schröder, M Picheral Workshop on Machine Learning in Marine Sciences, 2018 | | 2018 |
Quantitative image processing with machine learning: How to turn images into data JO Irisson, SM Schröder, M Picheral Aquatic research models to study regeneration and aging, 2018 | | 2018 |
Einfluss der mental map auf die Orientierung in dynamischen Graphen SM Schröder Layout-Algorithmen für Graphen, 30, 2013 | | 2013 |