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Object Detection Using Recurrent Neural Network And Concatenated Feature Map

机译:递归神经网络和级联特征图的目标检测

摘要

According to one embodiment, a system includes a sensor component and a detection component. The sensor component is configured to obtain a first stream of sensor data and a second stream of sensor data, wherein each of the first stream and second stream comprise a plurality of sensor frames. The detection component is configured to generate a concatenated feature map based on a sensor frame of a first type and a sensor frame of a second type. The detection component is configured to detect one or more objects based on the concatenated feature map. One or more of generating and detecting comprises generating or detecting using a neural network with a recurrent connection that feeds information about features or objects from previous frames.
机译:根据一个实施例,一种系统包括传感器组件和检测组件。传感器组件被配置为获得传感器数据的第一流和传感器数据的第二流,其中第一流和第二流中的每一个包括多个传感器帧。所述检测组件被配置为基于第一类型的传感器框架和第二类型的传感器框架来生成级联特征图。所述检测组件被配置为基于所述级联特征图来检测一个或多个对象。生成和检测中的一个或多个步骤包括使用具有递归连接的神经网络生成或检测,该递归连接从前一帧馈送有关特征或对象的信息。

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