首页> 外国专利> OFFLINE COMBINATION OF CONVOLUTION/DE-CONVOLUTION LAYER AND BATCH NORMALIZATION LAYER OF CONVOLUTION NEUTRAL NETWORK MODEL USED FOR AUTOMATIC DRIVING VEHICLE

OFFLINE COMBINATION OF CONVOLUTION/DE-CONVOLUTION LAYER AND BATCH NORMALIZATION LAYER OF CONVOLUTION NEUTRAL NETWORK MODEL USED FOR AUTOMATIC DRIVING VEHICLE

机译:用于自动驾驶汽车的卷积神经网络模型的卷积/去卷积层和批量归一化层的离线组合

摘要

PROBLEM TO BE SOLVED: To provide a system of convolution neutral network (CNN) model of accelerated batch normalization capable of being used in an automatic driving vehicle.SOLUTION: The system extracts a plurality of first layer groups from a first CNN model and each group includes a first convolution layer and a first batch normalization layer. Regarding each group, the system calculates a first scale vector and a first shift vector on the basis of the first batch normalization layer and generates a second convolution layer showing a corresponding group in the plurality of first groups on the basis of the first convolution layer, the first scale vector and the first shift vector. In addition, the system generates an accelerated CNN model on the basis of the second convolution layer corresponding to the plurality of first groups and classifies targets detected by an automatic driving vehicle.SELECTED DRAWING: Figure 9
机译:解决的问题:提供一种能够在自动驾驶车辆中使用的加速批归一化的卷积神经网络(CNN)模型。解决方案:该系统从第一CNN模型中提取多个第一层组,每个组包括第一卷积层和第一批归一化层。对于每个组,系统基于第一批归一化层计算第一比例矢量和第一移位矢量,并基于第一卷积层生成第二卷积层,该第二卷积层示出了多个第一组中的对应组,第一比例向量和第一位移向量。另外,该系统基于与多个第一组相对应的第二卷积层生成加速的CNN模型,并对自动驾驶车辆检测到的目标进行分类。图9

著录项

  • 公开/公告号JP2018173946A

    专利类型

  • 公开/公告日2018-11-08

    原文格式PDF

  • 申请/专利权人 BAIDU USA LLC;

    申请/专利号JP20180039360

  • 申请日2018-03-06

  • 分类号G08G1/16;G06N3/04;G06T7;G01C21/26;

  • 国家 JP

  • 入库时间 2022-08-21 13:13:07

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