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Linus Mathias Scheibenreif
Toward Global Estimation of Ground-Level NO2 Pollution With Deep Learning and Remote Sensing
Self-supervised Vision Transformers for Land-cover Segmentation and Classification
Power Plant Classification from Remote Imaging with Deep Learning
Characterization of Industrial Smoke Plumes from Remote Sensing Data
Masked Vision Transformers for Hyperspectral Image Classification
Contrastive Self-Supervised Data Fusion for Satellite Imagery
A Novel Dataset and Benchmark for Surface NO2 Prediction from Remote Sensing Data Including COVID Lockdown Measures
A Multimodal Approach for Event Detection: Study of UK Lockdowns in the Year 2020.
Multitask Learning for Estimating Power Plant Greenhouse Gas Emissions from Satellite Imagery
Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space