In various examples, systems and methods are disclosed that use one or more machine learning models (MLMs) - such as deep neural networks (DNNs) - to compute outputs indicative of an estimated visibility distance corresponding to sensor data generated using one or more sensors of an autonomous or semi-autonomous machine. Once the visibility distance is computed using the one or more MLMs, a determination of the usability of the sensor data for one or more downstream tasks of the machine may be evaluated. As such, where an estimated visibility distance is low, the corresponding sensor data may be relied upon for less tasks than when the visibility distance is high.


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    Titel :

    VISIBILITY DISTANCE ESTIMATION USING DEEP LEARNING IN AUTONOMOUS MACHINE APPLICATIONS


    Beteiligte:
    BAJPAYEE ABHISHEK (Autor:in) / GUPTA ARJUN (Autor:in) / TANG GEORGE (Autor:in) / SEO HAE-JONG (Autor:in)

    Erscheinungsdatum :

    13.04.2023


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion



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