A system for faster object attribute and/or intent classification may include a machine learning (ML) architecture that processes temporal sensor data (e.g., multiple instances of sensor data received at different times) and includes a cache in an intermediate layer of the ML architecture. The ML architecture may be capable of classifying an intention of an object to enter a roadway, to be in an idle state near the roadway, or to actively pass through the roadway. The ML architecture may additionally or alternatively classify indicator states (e.g., indications of steering, stop, etc.). Other attributes and/or intent are discussed herein.

    一种用于较快的对象属性和/或意图分类的系统可以包括机器学习(ML)架构,该ML架构处理时间传感器数据(例如,在不同时间接收到的传感器数据的多个实例)并且包括该ML架构的中间层中的高速缓存。ML架构可以能够对对象进入道路、在道路附近处于空闲状态或者主动穿过道路的意图进行分类。ML架构可以另外地或者可替代地对指示器状态(例如,转向、停止的指示等)进行分类。本文讨论了其他属性和/或意图。


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    Title :

    Machine learning architecture for efficient object attribute and/or intent classification


    Additional title:

    用于高效的对象属性和/或意图分类的机器学习架构


    Contributors:
    DAS SOUMYA (author) / LIN YI-TING (author) / MA DAVID X (author) / ULUTAIN OZGUR (author)

    Publication date :

    2024-06-18


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06V / 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 / B60T Bremsanlagen für Fahrzeuge oder Teile davon , VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF



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