25–27 Mar 2025
European Space Research and Technology Centre (ESTEC)
Europe/Amsterdam timezone
Draft Agenda published

Session

Artificial Intelligence/Machine Learning

26 Mar 2025, 11:45
Newton 1 and 2 (European Space Research and Technology Centre (ESTEC))

Newton 1 and 2

European Space Research and Technology Centre (ESTEC)

Keplerlaan 1 2201AZ Noordwijk ZH The Netherlands

Presentation materials

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  1. Marko Mamić (Protostar Labs), Mr Filip Gembec (Protostar Labs)
    26/03/2025, 11:45
    Artificial Intelligence/Machine Learning
    Oral presentation

    ProtoSDK is a low-code software development kit (SDK) aimed at simplifying the deployment of deep learning (DL) models on FPGA-based devices for space-related applications. By removing the necessity for specialized programming knowledge, ProtoSDK enhances accessibility and facilitates seamless workflows from selecting a model to deploying it on an FPGA.

    The SDK enables an end user to select...

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  2. Mr Daniel Fortun (GMV GmbH)
    26/03/2025, 12:10
    Artificial Intelligence/Machine Learning
    Oral presentation

    The space ecosystem is rapidly evolving, driven by the New Space paradigm, which emphasizes the use of commercial off-the-shelf (COTS) components and more powerful, reconfigurable payloads. This shift enables missions to dynamically adapt and enhance their capabilities in orbit. However, reconfigurable architectures based on SRAM-based FPGAs introduce security challenges, particularly...

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  3. Mr Matteo Monopoli (University of Pisa), Ms Gabriela Mystkowska (University of Pisa)
    26/03/2025, 12:35
    Artificial Intelligence/Machine Learning
    Oral presentation

    In recent years, the role of Artificial Intelligence (AI) has become increasingly prominent in the space industry. Its ability to perform better than traditional methods, in particular for image processing, has further accelerated its development within the sector. In this context, the architecture of a spacecraft’s processing system is crucial in determining both the efficiency of inference...

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