The search for life beyond Earth can benefit from orbiters and spacecraft with compact instruments able to identify potential biological signatures. One of the main challenges is the balance between a lower resolution and a wide field of view to discard uninteresting places while a high resolution - narrow field of view to collect data in higher detail. The recent flights of the Mars helicopter “Ingenuity” have shown UAVs are a viable platform to explore the surface of celestial objects in a wide and narrow approach using diverse remote sensing instruments. With data collected from real biosignatures in Western Australia, this work proposes an online UAV-based Artificial Intelligence detector using Convolutional Neural Networks (CNN) based on ResNet18 and YOLO models able to detect multiple potential biological signatures in near real-time. The system and pipeline presented allow the inclusion of new observations refined by scientists to increase the scientific exploration outcomes for remote-based operations.


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    Titel :

    Towards a Biosignatures Image Detection System for Planetary Exploration with UAVs


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    04.03.2023


    Format / Umfang :

    13234056 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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