Stefan Oehmcke

According to our database, Stefan Oehmcke authored at least 34 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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

MMEarth: Exploring Multi-modal Pretext Tasks for Geospatial Representation Learning.

Vishal Nedungadi, Ankit Kariryaa, Stefan Oehmcke, Serge J. Belongie, Christian Igel, Nico Lang

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Multi-scale pseudo labeling for unsupervised deep edge detection.

Changsheng Zhou, Chao Yuan, Hongxin Wang, Lei Li, Stefan Oehmcke, Junmin Liu, Jigen Peng

Knowl. Based Syst., November, 2023

Remember to Correct the Bias When Using Deep Learning for Regression!

Christian Igel, Stefan Oehmcke

Künstliche Intell., March, 2023

BuildSeg: A General Framework for the Segmentation of Buildings.

Lei Li, Tianfang Zhang, Stefan Oehmcke, Fabian Gieseke, Christian Igel

CoRR, 2023

Predicting urban tree cover from incomplete point labels and limited background information.

Hui Zhang, Ankit Kariryaa, Venkanna Babu Guthula, Christian Igel, Stefan Oehmcke

Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI, 2023

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

Proceedings of the IEEE International Conference on Big Data, 2023

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, Christian Igel, Fabian Gieseke, Thomas Friborg

Remote. Sens., 2022

LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing.

Tianfang Zhang, Lei Li, Christian Igel, Stefan Oehmcke, Fabian Gieseke, Zhenming Peng

CoRR, 2022

Input Selection for Bandwidth-Limited Neural Network Inference.

Stefan Oehmcke, Fabian Gieseke

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Deep learning based 3D point cloud regression for estimating forest biomass.

Stefan Oehmcke, Lei Li, Jaime C. Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, Christian Igel

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

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

Attentional Feature Fusion.

Yimian Dai, Fabian Gieseke, Stefan Oehmcke, Yiquan Wu, Kobus Barnard

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Estimating Forest Canopy Height With Multi-Spectral and Multi-Temporal Imagery Using Deep Learning.

Stefan Oehmcke, Thomas Nyegaard-Signori, Kenneth Grogan, Fabian Gieseke

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Attention as Activation.

Yimian Dai, Stefan Oehmcke, Yiquan Wu, Kobus Barnard

CoRR, 2020

Modeling H2O/Rutile-TiO2(110) Potential Energy Surfaces with Deep Networks.

Stefan Oehmcke, Thomas Teusch, Thorben Petersen, Thorsten Klüner, Oliver Kramer

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Attention as Activation.

Yimian Dai, Stefan Oehmcke, Fabian Gieseke, Yiquan Wu, Kobus Barnard

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Creating cloud-free satellite imagery from image time series with deep learning.

Stefan Oehmcke, Tzu-Hsin Karen Chen, Alexander V. Prishchepov, Fabian Gieseke

Proceedings of the BIGSPATIAL '20: Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, 2020

2019

Learning Selection Masks for Deep Neural Networks.

Stefan Oehmcke, Fabian Gieseke

CoRR, 2019

Evolution of Stacked Autoencoders.

Tim Silhan, Stefan Oehmcke, Oliver Kramer

Proceedings of the IEEE Congress on Evolutionary Computation, 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

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Magnitude and Uncertainty Pruning Criterion for Neural Networks.

Vinnie Ko, Stefan Oehmcke, Fabian Gieseke

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Deep learning of virtual marine sensors.

Stefan Oehmcke

PhD thesis, 2018

Input quality aware convolutional LSTM networks for virtual marine sensors.

Stefan Oehmcke, Oliver Zielinski, Oliver Kramer

Neurocomputing, 2018

Knowledge Sharing for Population Based Neural Network Training.

Stefan Oehmcke, Oliver Kramer

Proceedings of the KI 2018: Advances in Artificial Intelligence, 2018

Direct Training of Dynamic Observation Noise with UMarineNet.

Stefan Oehmcke, Oliver Zielinski, Oliver Kramer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

2017

Recurrent neural networks and exponential PAA for virtual marine sensors.

Stefan Oehmcke, Oliver Zielinski, Oliver Kramer

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Manifold learning with iterative dimensionality photo-projection.

Daniel Lückehe, Stefan Oehmcke, Oliver Kramer

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Spatio-Temporal Wind Power Prediction Using Recurrent Neural Networks.

Wei Lee Woon, Stefan Oehmcke, Oliver Kramer

Proceedings of the Neural Information Processing - 24th International Conference, 2017

Preferences-Based Choice Prediction in Evolutionary Multi-objective Optimization.

Manish Aggarwal, Justin Heinermann, Stefan Oehmcke, Oliver Kramer

Proceedings of the Applications of Evolutionary Computation - 20th European Conference, 2017

2016

kNN ensembles with penalized DTW for multivariate time series imputation.

Stefan Oehmcke, Oliver Zielinski, Oliver Kramer

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

Event Detection in Marine Time Series Data.

Stefan Oehmcke, Oliver Zielinski, Oliver Kramer

Proceedings of the KI 2015: Advances in Artificial Intelligence, 2015

Analysis of Diversity Methods for Evolutionary Multi-objective Ensemble Classifiers.

Stefan Oehmcke, Justin Heinermann, Oliver Kramer

Proceedings of the Applications of Evolutionary Computation - 18th European Conference, 2015

2013

Storyteller: in-situ reflection on study experiences.

Benjamin Poppinga, Stefan Oehmcke, Wilko Heuten, Susanne Boll

Proceedings of the 15th International Conference on Human-Computer Interaction with Mobile Devices and Services, 2013