In space you must live with what you have! In the data-centric machine learning challenge "the OPS-SAT case" you are given a (quantized) neural model that has passed all the requirements for inference on-board the European Space Agency's satellite OPS-SAT. Can you train its parameters as to predict one of eight classes for some tile coming directly from the spacecraft imaging sensor? .... ah, there is a catch, you will not have as many labels to work with as you would like!

On the bright side, should you be brave enough and succeed in this few-shots learning, quantization aware challenge, you will be given access to the satellite, your model uploaded and used for inferences during a real time, dedicated observational campaign! 

This competition is created and organized by the Advanced Concepts Team (ACT) with collaborations from Phi-Lab and the OPS-SAT spacecraft operations team.

Experts from both teams are available for interactions via the competition discussion page.