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SYSTEM AND METHOD FOR SENSOR FUSION SYSTEM HAVING DISTRIBUTED CONVOLUTIONAL NEURAL NETWORK

机译:具有分布式卷积神经网络的传感器融合系统的系统和方法

摘要

An early fusion network is provided that reduces network load and enables easier design of specialized ASIC edge processors through performing a portion of convolutional neural network layers at distributed edge and data-network processors prior to transmitting data to a centralized processor for fully-connected/deconvolutional neural networking processing. Embodiments can provide convolution and downsampling layer processing in association with the digital signal processors associated with edge sensors. Once the raw data is reduced to smaller feature maps through the convolution-downsampling process, this reduced data is transmitted to a central processor for further processing such as regression, classification, and segmentation, along with feature combination of the data from the sensors. In some embodiments, feature combination can be distributed to gateway or switch nodes closer to the edge sensors, thereby further reducing the data transferred to the central node and reducing the amount of computation performed there.
机译:提供了早期融合网络,其通过在分布边缘和数据网络处理器处执行分布式边缘和数据网络处理器的一部分通过在将数据传输到集中式处理器以进行全连接/解卷积的集中式处理器,使网络负载减少网络负载并且能够更容易地设计专业的ASIC边缘处理器。神经网络处理。实施例可以与与边缘传感器相关联的数字信号处理器相关联地提供卷积和下采样层处理。一旦原始数据通过卷积下采样过程减少到较小的特征映射,就会将其减少的数据传输到中央处理器,以便进一步处理,例如回归,分类和分割,以及来自传感器的数据的特征组合。在一些实施例中,特征组合可以分配给靠近边缘传感器的网关或开关节点,从而进一步将传送到中心节点传输的数据并减少在那里执行的计算量。

著录项

  • 公开/公告号EP3929807A1

    专利类型

  • 公开/公告日2021-12-29

    原文格式PDF

  • 申请/专利权人 NXP USA INC.;

    申请/专利号EP20210178070

  • 发明设计人 WU RYAN HAOYUN;RAVINDRAN SATISH;FUKS ADAM;

    申请日2021-06-07

  • 分类号G06K9;G06K9/46;G06K9/62;

  • 国家 EP

  • 入库时间 2022-08-24 23:05:35

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