Stefan Oehmcke
Adjunkt
- Udgivet
LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing
Zhang, T., Li, Lei, Igel, Christian, Oehmcke, Stefan, Gieseke, F. & Peng, Z., 2023, 2022 IEEE International Conference on Computer and Communications (ICCC), Chengdu, China. IEEE, s. 1951-1957Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
MAPPING TREE MORTALITY IN CALIFORNIA FROM VERY HIGH RESOLUTION IMAGERY USING DEEP LEARNING
Cheng, Yan, Oehmcke, Stefan, Brandt, Martin Stefan, Das, A., Rosenthal, L., Saatchi, S., Wagner, F., Vrieling, A., Verbruggen, Wim, Beier, Claus & Horion, Stéphanie, 2023.Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › fagfællebedømt
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Magnitude and Uncertainty Pruning Criterion for Neural Networks
Ko, V., Oehmcke, Stefan & Gieseke, Fabian Cristian, 2019, 2019 IEEE International Conference on Big Data, Big Data. Baru, C., Huan, J., Khan, L., Hu, X. T., Ak, R., Tian, Y., Barga, R., Zaniolo, C., Lee, K. & Ye, Y. F. (red.). IEEE, s. 2317-2326 9005692. (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Manifold learning with iterative dimensionality photo-projection
Luckehe, D., Oehmcke, Stefan & Kramer, O., 30 jun. 2017, 2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., s. 2555-2561 7 s. 7966167Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Mapping and characterising tree mortality in California at individual tree level using deep learning
Cheng, Yan, Oehmcke, Stefan, Brandt, Martin Stefan, Das, A., Rosenthal, L., Saatchi, S., Wagner, F., Verbruggen, Wim, Vrieling, A., Beier, Claus & Horion, Stéphanie, 2023. 1 s.Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning
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More than one quarter of Africa's tree cover is found outside areas previously classified as forest
Reiner, F., Brandt, M., Tong, X., Skole, D., Kariryaa, A., Ciais, P., Davies, A., Hiernaux, P., Chave, J., Mugabowindekwe, M., Igel, C., Oehmcke, S., Gieseke, F., Li, S., Liu, S., Saatchi, S., Boucher, P., Singh, J., Taugourdeau, S., Dendoncker, M. & 4 flere, , 2023, I: Nature Communications. 14, 10 s., 2258.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Multi-scale pseudo labeling for unsupervised deep edge detection
Zhou, C., Yuan, C., Wang, H., Li, Lei, Oehmcke, Stefan, Liu, J. & Peng, J., 2023, I: Knowledge-Based Systems. 280, 15 s., 111057.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Plant Structure and Carbon Storage Assessment Utilizing Drone-Borne Lidar and Deep Learning Technologies in a Danish Agricultural Expanse.
Trepekli, Aikaterini, Caballer Revenga, Jaime, Oehmcke, Stefan, Gieseke, Fabian Cristian, Jensen, Rasmus & Friborg, Thomas, 2021. 12 s.Publikation: Konferencebidrag › Paper › Forskning
- Udgivet
Predicting urban tree cover from incomplete point labels and limited background information
Zhang, Hui, Kariryaa, Ankit, Guthula, Venkanna Babu, Igel, Christian & Oehmcke, Stefan, 2023, Urban-AI 2023 - Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI. Omitaomu, O. A., Mostafavi, A. & Liu, Y. (red.). Association for Computing Machinery, Inc., s. 52-60Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Prediction of above ground biomass and C-stocks based on UAV-LiDAR,multispectral imagery and machine learning methods.
Caballer Revenga, Jaime, Trepekli, Aikaterini, Oehmcke, Stefan, Gieseke, Fabian Cristian, Jensen, Rasmus & Friborg, Thomas, 2021. 1 s.Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › fagfællebedømt
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Creating cloud-free satellite imagery from image time series with deep learning
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Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale
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Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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