Intelligent vehicles are becoming more and more common on our roads. They can perceive the surrounding environment, communicate with other vehicles, and even make decisions based on the collected information. However, these vehicles have a long way to go before they are considered "smart". In this paper, we will discuss how multimodal fusion target detection for ICV perception becomes an important part of the future auto drive system. Multimodal fusion is a technology that combines multiple sensory modes (such as vision and radar) to improve the performance of complex target detection. Multimodal fusion is a data fusion that combines different types of sensory data to detect objects or targets in the real world environment. It has been proved that multimodal fusion can detect multiple targets at the same time with high accuracy and low false alarm rate, which is superior to single-mode target detection method.


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    Titel :

    Multimodal Fusion Target Detection for Intelligent Connected Vehicle Sensing Module


    Beteiligte:
    Shuai, Yuan (Autor:in) / Yangxue, Shao (Autor:in) / Yun, Meng (Autor:in)


    Erscheinungsdatum :

    14.07.2023


    Format / Umfang :

    738850 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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