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Michael Mommert
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2020 – today
- 2024
- [j5]Nafiseh Kakhani, Moien Rangzan, Ali Jamali, Sara Attarchi, Seyed Kazem Alavipanah, Michael Mommert, Nikolaos Tziolas, Thomas Scholten:
SSL-SoilNet: A Hybrid Transformer-Based Framework With Self-Supervised Learning for Large-Scale Soil Organic Carbon Prediction. IEEE Trans. Geosci. Remote. Sens. 62: 1-15 (2024) - [c12]Linus Scheibenreif, Michael Mommert, Damian Borth:
Parameter Efficient Self-Supervised Geospatial Domain Adaptation. CVPR 2024: 27841-27851 - [c11]Nafiseh Kakhani, Michael Mommert, Thomas Scholten:
Advanced Prediction of Soil Organic Carbon: A Hybrid Transformer Network with Cost-Sensitive Learning Using Remote Sensing and Climate Data. IGARSS 2024: 1594-1598 - [c10]Alexander Lontke, Michael Mommert, Damian Borth:
Multi-Modal Diffusion for Self-Supervised Pretraining. IGARSS 2024: 2828-2832 - 2023
- [j4]Joëlle Hanna, Damian Borth, Michael Mommert:
Physics-Guided Multitask Learning for Estimating Power Generation and CO2 Emissions From Satellite Imagery. IEEE Trans. Geosci. Remote. Sens. 61: 1-12 (2023) - [c9]Joëlle Hanna, Michael Mommert, Damian Borth:
Sparse Multimodal Vision Transformer for Weakly Supervised Semantic Segmentation. CVPR Workshops 2023: 2145-2154 - [c8]Linus Scheibenreif, Michael Mommert, Damian Borth:
Masked Vision Transformers for Hyperspectral Image Classification. CVPR Workshops 2023: 2166-2176 - [c7]Julius Lautz, Daniel Leal, Linus Scheibenreif, Damian Borth, Michael Mommert:
Dataset Distillation for Eurosat. IGARSS 2023: 530-533 - [c6]Michael Mommert, Nicolas Kesseli, Joëlle Hanna, Linus Scheibenreif, Damian Borth, Begüm Demir:
Ben-Ge: Extending Bigearthnet with Geographical and Environmental Data. IGARSS 2023: 1016-1019 - [i4]Michael Mommert, Nicolas Kesseli, Joëlle Hanna, Linus Scheibenreif, Damian Borth, Begüm Demir:
Ben-ge: Extending BigEarthNet with Geographical and Environmental Data. CoRR abs/2307.01741 (2023) - 2022
- [j3]Linus Scheibenreif, Michael Mommert, Damian Borth:
Toward Global Estimation of Ground-Level NO2 Pollution With Deep Learning and Remote Sensing. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - [c5]Linus Scheibenreif, Joëlle Hanna, Michael Mommert, Damian Borth:
Self-supervised Vision Transformers for Land-cover Segmentation and Classification. CVPR Workshops 2022: 1421-1430 - [c4]Joëlle Hanna, Linus Scheibenreif, Michael Mommert, Damian Borth:
A Multimodal Approach for Event Detection: Study of UK Lockdowns in the Year 2020. IGARSS 2022: 715-718 - [c3]Leonardo Eicher, Michael Mommert, Damian Borth:
Traffic Noise Estimation from Satellite Imagery with Deep Learning. IGARSS 2022: 5937-5940 - 2021
- [c2]Michael Mommert, Linus Scheibenreif, Joëlle Hanna, Damian Borth:
Power Plant Classification from Remote Imaging with Deep Learning. IGARSS 2021: 6391-6394 - [c1]Linus Scheibenreif, Michael Mommert, Damian Borth:
A Novel Dataset and Benchmark for Surface No2 Prediction from Remote Sensing Data Including Covid Lockdown Measures. IGARSS 2021: 8364-8367 - [i3]Michael Mommert, Linus Scheibenreif, Joëlle Hanna, Damian Borth:
Power Plant Classification from Remote Imaging with Deep Learning. CoRR abs/2107.10894 (2021) - [i2]Linus Scheibenreif, Michael Mommert, Damian Borth:
Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space. CoRR abs/2108.13902 (2021) - 2020
- [i1]Michael Mommert, Mario Sigel, Marcel Neuhausler, Linus Scheibenreif, Damian Borth:
Characterization of Industrial Smoke Plumes from Remote Sensing Data. CoRR abs/2011.11344 (2020)
2010 – 2019
- 2019
- [j2]Michael Mommert, Michael S. P. Kelley, Miguel de Val-Borro, Jian-Yang Li, Giannina Guzman, Brigitta M. Sipocz, Josef Durech, Mikael Granvik, William S. Noble, Nick Moskovitz, Antti Penttilä, Nalin Samarasinha:
sbpy: A Python module for small-body planetary astronomy. J. Open Source Softw. 4(38): 1426 (2019) - 2017
- [j1]Michael Mommert:
PHOTOMETRYPIPELINE: An automated pipeline for calibrated photometry. Astron. Comput. 18: 47-53 (2017)
Coauthor Index
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last updated on 2024-10-08 21:30 CEST by the dblp team
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