Selected article for: "deep learning transferability problem and training scheme"
Author: Min Zhou; Yong Chen; Dexiang Wang; Yanping Xu; Weiwu Yao; Jingwen Huang; Xiaoyan Jin; Zilai Pan; Jingwen Tan; Lan Wang; Yihan Xia; Longkuan Zou; Xin Xu; Jingqi Wei; Mingxin Guan; Jianxing Feng; Huan Zhang; Jieming Qu
Title: Improved deep learning model for differentiating novel coronavirus pneumonia and influenza pneumonia
  • Document date: 2020_3_30
    • ID: ilc2bzkx_6
    Snippet: In this study, we developed and validated an integrated deep learning framework on chest CT images for auto-detection of NCP, particularly focusing on differentiating NCP from IP, ensuring prompt implementation of isolation. To alleviate transferability problem that a well-trained deep learning model performs poorly on data from unseen sources (16), we proposed a novel training scheme (Trinary scheme) to encourage the model to learn device indepe.....
    Document: In this study, we developed and validated an integrated deep learning framework on chest CT images for auto-detection of NCP, particularly focusing on differentiating NCP from IP, ensuring prompt implementation of isolation. To alleviate transferability problem that a well-trained deep learning model performs poorly on data from unseen sources (16), we proposed a novel training scheme (Trinary scheme) to encourage the model to learn device independent features.

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