A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.


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    Titel :

    Ensemble neural network state machine for detecting distractions


    Beteiligte:
    SRINIVASAN SHARAN (Autor:in) / TUAN BRIAN (Autor:in) / BICKET JOHN (Autor:in) / WANG JING (Autor:in) / AKHTAR MUHAMMAD ALI (Autor:in) / ACEVEDO ABNER AYALA (Autor:in) / KELLERMAN BRUCE (Autor:in) / SHIEH VINCENT (Autor:in)

    Erscheinungsdatum :

    12.07.2022


    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



    Ensemble neural network state machine for detecting distractions

    SRINIVASAN SHARAN / TUAN BRIAN / BICKET JOHN et al. | Europäisches Patentamt | 2024

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