Phi-week session

Sentinel-2 image courtesy of 

ESA Φ-week 2020 side-event:

Machine Learning for Operational Ice Charting

David Arthurs (Polar View): The Polar TEP Machine Learning Platform

Anton Korosov (NERSC): NERSC Sea Ice Type Classification using CNN

Juha Karvonen (FMI): Sea ice concentration estimation based on SAR segmentation and CNNs

Andrea Scott (University Of Waterloo): Detection of marginal ice zone features using SAR and DL

Jeff Bartz (C-CORE): Land Fast Ice in the Canadian Arctic using SAR

Gordon Davidson (MDA Systems): Sea Ice Monitoring Using RADARSAT-2 and Deep Learning

Matilde Brandt Kreiner (DMI): The ASIP / AI4Arctic sea ice dataset for machine learning applications

David Malmgren-Hansen (DTU): Fusion of Sentinel-1 and AMSR2 with CNNs for Regression of Sea Ice Concentrations

Theofilos Kakantousis (Logical Clocks AB): Building DL Pipelines for Copernicus Data using Hopsworks on CREODIAS: ExtremeEarth Polar Use Case

Habib Ullah (UiT): Synthetic aperture radar data analysis by DL for automaticsea ice classification

Corneliu Octavian Dumitru (DLR): Comparison of Efficient Ice Mapping Algorithms for Satellite Images

Alexander Komarov (ECCC): Automated retrieval of ice information from SAR for data assimilation

Session 3 - posters, discussion: Thursday 01 October 16:30-18:00 CEST

Joakim Lillehaug Pedersen (Met Norway): Deep Learning for sea ice

Thomas Kræmer (UIT): Towards automated ice charts using Copernicus data

Jørgen Buus-Hinkler (DMI): Pre- and post-processing of input and output data for CNNs

Suman Singha (DLR): Towards Pan-Arctic Sea Ice Type Retrieval using Sentinel-1