In various examples, live perception from sensors of a vehicle may be leveraged to detect and classify intersections in an environment of a vehicle in real-time or near real-time. For example, a deep neural network (DNN) may be trained to compute various outputs—such as bounding box coordinates for intersections, intersection coverage maps corresponding to the bounding boxes, intersection attributes, distances to intersections, and/or distance coverage maps associated with the intersections. The outputs may be decoded and/or post-processed to determine final locations of, distances to, and/or attributes of the detected intersections.


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    Titel :

    INTERSECTION DETECTION AND CLASSIFICATION IN AUTONOMOUS MACHINE APPLICATIONS


    Beteiligte:
    SAJJADI MOHAMMADABADI SAYED MEHDI (Autor:in) / RODRIGUEZ HERVAS BERTA (Autor:in) / DOU HANG (Autor:in) / TRYNDIN IGOR (Autor:in) / NISTER DAVID (Autor:in) / PARK MINWOO (Autor:in) / CVIJETIC NEDA (Autor:in) / KWON JUNGHYUN (Autor:in) / PHAM TRUNG (Autor:in)

    Erscheinungsdatum :

    2023-06-01


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06V / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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