Storyteller: in-situ reflection on study experiences. - Benjamin Poppinga; Stefan Oehmcke; Wilko Heuten; Susanne Boll (Mobile HCI, 2013)

Analysis of Diversity Methods for Evolutionary Multi-objective Ensemble Classifiers. - Stefan Oehmcke; Justin Heinermann; Oliver Kramer 001 (EvoApplications, 2015)

Event Detection in Marine Time Series Data. - Stefan Oehmcke; Oliver Zielinski; Oliver Kramer 001 (KI, 2015)

kNN ensembles with penalized DTW for multivariate time series imputation. - Stefan Oehmcke; Oliver Zielinski; Oliver Kramer 001 (IJCNN, 2016)

Preferences-Based Choice Prediction in Evolutionary Multi-objective Optimization. - Manish Aggarwal; Justin Heinermann; Stefan Oehmcke; Oliver Kramer 001 (EvoApplications (1), 2017)

Spatio-Temporal Wind Power Prediction Using Recurrent Neural Networks. - Wei Lee Woon; Stefan Oehmcke; Oliver Kramer 001 (ICONIP (5), 2017)

Manifold learning with iterative dimensionality photo-projection. - Daniel Lückehe; Stefan Oehmcke; Oliver Kramer 001 (IJCNN, 2017)

Recurrent neural networks and exponential PAA for virtual marine sensors. - Stefan Oehmcke; Oliver Zielinski; Oliver Kramer 001 (IJCNN, 2017)

Direct Training of Dynamic Observation Noise with UMarineNet. - Stefan Oehmcke; Oliver Zielinski; Oliver Kramer 001 (ICANN (1), 2018)

Knowledge Sharing for Population Based Neural Network Training. - Stefan Oehmcke; Oliver Kramer 001 (KI, 2018)

Input quality aware convolutional LSTM networks for virtual marine sensors. - Stefan Oehmcke; Oliver Zielinski; Oliver Kramer 001 (Neurocomputing, 2018)

Deep learning of virtual marine sensors. - Stefan Oehmcke (2018)

Magnitude and Uncertainty Pruning Criterion for Neural Networks. - Vinnie Ko; Stefan Oehmcke; Fabian Gieseke (IEEE BigData, 2019)

Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data. - Stefan Oehmcke; Christoffer Thrysøe; Andreas Borgstad; Marcos Antonio Vaz Salles; Martin Brandt; Fabian Gieseke (IEEE BigData, 2019)

Evolution of Stacked Autoencoders. - Tim Silhan; Stefan Oehmcke; Oliver Kramer 001 (CEC, 2019)

Learning Selection Masks for Deep Neural Networks. - Stefan Oehmcke; Fabian Gieseke (CoRR, 2019)

Creating cloud-free satellite imagery from image time series with deep learning. - Stefan Oehmcke; Tzu-Hsin Karen Chen; Alexander V. Prishchepov; Fabian Gieseke (BigSpatial@SIGSPATIAL, 2020)

Attention as Activation. - Yimian Dai; Stefan Oehmcke; Fabian Gieseke; Yiquan Wu; Kobus Barnard (ICPR, 2020)

Modeling H2O/Rutile-TiO2(110) Potential Energy Surfaces with Deep Networks. - Stefan Oehmcke; Thomas Teusch; Thorben Petersen; Thorsten Klüner; Oliver Kramer 001 (IJCNN, 2020)

Attention as Activation. - Yimian Dai; Stefan Oehmcke; Yiquan Wu; Kobus Barnard (CoRR, 2020)

Estimating Forest Canopy Height With Multi-Spectral and Multi-Temporal Imagery Using Deep Learning. - Stefan Oehmcke; Thomas Nyegaard-Signori; Kenneth Grogan; Fabian Gieseke (IEEE BigData, 2021)

Attentional Feature Fusion. - Yimian Dai; Fabian Gieseke; Stefan Oehmcke; Yiquan Wu; Kobus Barnard (WACV, 2021)

Both sides of the story: comparing student-level data on reading performance from administrative registers to application generated data from a reading app. - Bent Sortkær; Emil Smith; David Reimer; Stefan Oehmcke; Ida Gran Andersen (EPJ Data Sci., 2021)

Deep learning based 3D point cloud regression for estimating forest biomass. - Stefan Oehmcke; Lei Li 050; Jaime C. Revenga; Thomas Nord-Larsen; Katerina Trepekli; Fabian Gieseke; Christian Igel (SIGSPATIAL/GIS, 2022)

Input Selection for Bandwidth-Limited Neural Network Inference. - Stefan Oehmcke; Fabian Gieseke (SDM, 2022)

LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing. - Tianfang Zhang; Lei Li 050; Christian Igel; Stefan Oehmcke; Fabian Gieseke; Zhenming Peng (CoRR, 2022)

Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods. - Jaime C. Revenga; Katerina Trepekli; Stefan Oehmcke; Rasmus Jensen; Lei Li 050; Christian Igel; Fabian Gieseke; Thomas Friborg (Remote. Sens., 2022)

Seasonal-Trend Time Series Decomposition on Graphics Processing Units. - Dmitry Serykh; Stefan Oehmcke; Cosmin E. Oancea; Dainius Masiliunas; Jan Verbesselt; Yan Cheng; Stéphanie Horion; Fabian Gieseke; Nikolaj Hinnerskov (IEEE Big Data, 2023)

Predicting urban tree cover from incomplete point labels and limited background information. - Hui Zhang; Ankit Kariryaa; Venkanna Babu Guthula; Christian Igel; Stefan Oehmcke (UrbanAI@SIGSPATIAL, 2023)

BuildSeg: A General Framework for the Segmentation of Buildings. - Lei Li 050; Tianfang Zhang; Stefan Oehmcke; Fabian Gieseke; Christian Igel (CoRR, 2023)

Remember to Correct the Bias When Using Deep Learning for Regression! - Christian Igel; Stefan Oehmcke (Künstliche Intell., 2023)

Multi-scale pseudo labeling for unsupervised deep edge detection. - Changsheng Zhou; Chao Yuan; Hongxin Wang; Lei Li 050; Stefan Oehmcke; Junmin Liu; Jigen Peng (Knowl. Based Syst., 2023)

MMEarth: Exploring Multi-modal Pretext Tasks for Geospatial Representation Learning. - Vishal Nedungadi; Ankit Kariryaa; Stefan Oehmcke; Serge J. Belongie; Christian Igel; Nico Lang (ECCV (64), 2024)

Nacala-Roof-Material: Drone Imagery for Roof Detection, Classification, and Segmentation to Support Mosquito-borne Disease Risk Assessment. - Venkanna Babu Guthula; Stefan Oehmcke; Remigio Chilaule; Hui Zhang; Nico Lang; Ankit Kariryaa; Johan Mottelson; Christian Igel (CoRR, 2024)

Multi-modal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds. - Simon Buus Jensen; Stefan Oehmcke; Andreas Møgelmose; Meysam Madadi; Christian Igel; Sergio Escalera; Thomas B. Moeslund (CoRR, 2025)