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Low power consumption deep neural network for simultaneous object detection and semantic segmentation in images on a mobile computing device

机译:低功耗深度神经网络,用于移动计算设备上的图像中的同步对象检测和语义分割

摘要

A mobile computing device receives an image from a camera physically located within a vehicle. The mobile computing device inputs the image into a convolutional model that generates a set of object detections and a set of segmented environment blocks in the image. The convolutional model includes subsets of encoding and decoding layers, as well as parameters associated with the layers. The convolutional model relates the image and parameters to the sets of object detections and segmented environment blocks. A server that stores object detections and segmented environment blocks is updated with the sets of object detections and segmented environment blocks detected in the image.
机译:移动计算设备从物理上位于车辆内的摄像机接收图像。移动计算设备将图像输入到卷积模型中,该模型生成图像中的一组对象检测和一组分段环境块。卷积模型包括编码和解码层的子集,以及与层相关联的参数。卷积模型将图像和参数涉及对象检测集和分段环境块。使用图像中检测到的对象检测集和分段环境块存储对象检测和分段环境块的服务器。

著录项

  • 公开/公告号US11010641B2

    专利类型

  • 公开/公告日2021-05-18

    原文格式PDF

  • 申请/专利权人 MAPBOX INC.;

    申请/专利号US201916354108

  • 发明设计人 ALEKSANDR BUSLAEV;

    申请日2019-03-14

  • 分类号G06K9/62;

  • 国家 US

  • 入库时间 2022-08-24 18:43:15

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