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Video s3
    Details
    Presenter(s)
    Kai Meng Headshot
    Display Name
    Kai Meng
    Affiliation
    Affiliation
    Fudan University
    Country
    Author(s)
    Display Name
    Bohong Yang
    Affiliation
    Affiliation
    Fudan University
    Display Name
    Kai Meng
    Affiliation
    Affiliation
    Fudan University
    Display Name
    Hong Lu
    Affiliation
    Affiliation
    Fudan University
    Display Name
    Xing Zhu
    Affiliation
    Affiliation
    Jihua laboratory
    Display Name
    Jingjing Luo
    Affiliation
    Affiliation
    Fudan University
    Abstract

    Pulse localization is the basic task of the pulse diagnosis with robot. Using neural network for localization can not only reduce the contact between the machine and the subject, reduce the discomfort of the process, but also reduce the preparation.We propose a novel method,spoon fully Convolutional networks (SFCN) with the landmarkfitting method for pulse localization. SFCN includes the fully Convolutional networks which is like the spoon. While the landmark fitting method find the pulse in the sub-pixels.

    Slides
    • SFCN: Spoon Fully Convolutional Networks for Pulse Localization (application/pdf)