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SYSTEMS AND METHODS FOR KEYPOINT DETECTION WITH CONVOLUTIONAL NEURAL NETWORKS

机译:卷积神经网络的关键点检测系统和方法

摘要

A keypoint detection system includes: a camera system including at least one camera; and a processor and memory, the processor and memory being configured to: receive an image captured by the camera system; compute a plurality of keypoints in the image using a convolutional neural network including: a first layer implementing a first convolutional kernel; a second layer implementing a second convolutional kernel; an output layer; and a plurality of connections between the first layer and the second layer and between the second layer and the output layer, each of the connections having a corresponding weight stored in the memory; and output the plurality of keypoints of the image computed by the convolutional neural network.
机译:关键点检测系统包括:包括至少一个摄像机的摄像机系统;以及处理器和存储器,所述处理器和存储器被配置为:接收由所述照相机系统捕获的图像;以及使用卷积神经网络计算图像中的多个关键点,该卷积神经网络包括:实现第一卷积核的第一层;以及第二层实现第二个卷积内核;输出层;第一层与第二层之间以及第二层与输出层之间的多个连接,每个连接具有存储在存储器中的相应权重;并输出由卷积神经网络计算出的图像的多个关键点。

著录项

  • 公开/公告号US2018268256A1

    专利类型

  • 公开/公告日2018-09-20

    原文格式PDF

  • 申请/专利权人 AQUIFI INC.;

    申请/专利号US201815924162

  • 发明设计人 KINH TIEU;CARLO DAL MUTTO;PAOLO DI FEBBO;

    申请日2018-03-16

  • 分类号G06K9/62;G06N3/08;G06K9/46;G06T7/00;

  • 国家 US

  • 入库时间 2022-08-21 13:00:32

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