Embodiments of the present disclosure comprise systems and methods that implement domain adaptation. For example, some embodiments may improve standard machine learning systems by providing a best estimation of unknown situations using existing trained models. The trained models may be adapted to use in new scenarios that might not have been identified during the training phase of the machine learning. Using this adaptive approach, the model can help the vehicle system prepare a best estimate of the environment that was not identified during training and take an appropriate action.


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    Titel :

    Confidence-estimated domain adaptation for training machine learning models


    Beteiligte:
    ROSMAN GUY (Autor:in)

    Erscheinungsdatum :

    29.08.2023


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06V / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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