首页> 外国专利> Learning method and learning device for training an object detection network by using attention maps and testing method and testing device using the same

Learning method and learning device for training an object detection network by using attention maps and testing method and testing device using the same

机译:学习方法和学习设备通过使用注意映射和测试方法和测试设备使用相同的测试方法培训对象检测网络

摘要

A method for training an object detection network by using attention maps is provided. The method includes steps of: (a) an on-device learning device inputting the training images into a feature extraction network, inputting outputs of the feature extraction network into a attention network and a concatenation layer, and inputting outputs of the attention network into the concatenation layer; (b) the on-device learning device inputting outputs of the concatenation layer into an RPN and an ROI pooling layer, inputting outputs of the RPN into a binary convertor and the ROI pooling layer, and inputting outputs of the ROI pooling layer into a detection network and thus to output object detection data; and (c) the on-device learning device train at least one of the feature extraction network, the detection network, the RPN and the attention network through backpropagations using an object detection losses, an RPN losses, and a cross-entropy losses.
机译:提供了通过使用注意图训练对象检测网络的方法。该方法包括以下步骤:(a)将训练图像输入到特征提取网络的设备上学习设备,将特征提取网络的输出输入注意网络和倾斜层,并将注意力网络的输出输入到其中级联层; (b)将替代层的On-Device学习设备输入RPN和ROI池层的输出输入,将RPN的输出输入二进制转换器和ROI池层,并将ROI池层的输出输入检测到检测网络,从而输出对象检测数据; (c)使用物体检测损耗,RPN损耗和跨熵损失,通过反向化特征提取网络,检测网络,RPN和注意网络中的至少一个特征提取网络,检测网络,RPN和注意网络。

著录项

  • 公开/公告号US10970598B1

    专利类型

  • 公开/公告日2021-04-06

    原文格式PDF

  • 申请/专利权人 STRADVISION INC.;

    申请/专利号US202017112413

  • 申请日2020-12-04

  • 分类号G06K9/62;G06N3/08;G06K9/32;G06N3/04;G06K9;

  • 国家 US

  • 入库时间 2022-08-24 18:04:45

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