9 citations · 17 across the 14 of their papers we have counts for
6 papers · 1 filter
Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space
Mikolaj Czerkawski, Marcin Kluczek, Jędrzej S. Bojanowski
With the ever-increasing volumes of the Earth observation data present in the archives of large programmes such as Copernicus, there is a growing need for efficient vector represen…
IceCloudNet: 3D reconstruction of cloud ice from Meteosat SEVIRI
Kai Jeggle, Mikolaj Czerkawski, Federico Serva +3
IceCloudNet is a novel method based on machine learning able to predict high-quality vertically resolved cloud ice water contents (IWC) and ice crystal number concentrations (N$_\t…
Non-invasive Diver Respiration Rate Monitoring in Hyperbaric Lifeboat Environments using Short-Range Radar
Mikolaj Czerkawski, Fraser Stewart, Christos Ilioudis +8
The monitoring of diver health during emergency events is crucial to ensuring the safety of personnel. A non-invasive system continuously providing a measure of the respiration rat…
A Novel Micro-Doppler Coherence Loss for Deep Learning Radar Applications
Mikolaj Czerkawski, Christos Ilioudis, Carmine Clemente +3
Deep learning techniques are subject to increasing adoption for a wide range of micro-Doppler applications, where predictions need to be made based on time-frequency signal represe…
Robustness of Deep Neural Networks for Micro-Doppler Radar Classification
Mikolaj Czerkawski, Carmine Clemente, Craig Michie +1
With the great capabilities of deep classifiers for radar data processing come the risks of learning dataset-specific features that do not generalize well. In this work, the robust…
Major TOM: Expandable Datasets for Earth Observation
Alistair Francis, Mikolaj Czerkawski
Deep learning models are increasingly data-hungry, requiring significant resources to collect and compile the datasets needed to train them, with Earth Observation (EO) models bein…