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Updated: Sep 25, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
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Deep Learning From Multiple Noisy Annotators as A Union.

Hongxin Wei, Renchunzi Xie, Lei Feng

    IEEE Transactions on Neural Networks and Learning Systems
    |April 29, 2022
    PubMed
    Summary
    This summary is machine-generated.

    UnionNet offers a novel deep learning approach for crowdsourced data annotation, improving consistency and efficiency. This method effectively coordinates multiple annotators by treating all labels as a union for direct neural network training.

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    Last Updated: Sep 25, 2025

    Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
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    Area of Science:

    • Machine Learning
    • Data Science
    • Computer Vision

    Background:

    • Crowdsourcing is widely used for large-scale data annotation.
    • Existing deep learning methods for crowdsourcing face limitations in learning consistency and computational efficiency.

    Purpose of the Study:

    • To introduce UnionNet, a novel method for learning from crowdsourced data.
    • To address the limitations of existing methods by improving theoretical consistency, effectiveness, and efficiency.

    Main Methods:

    • UnionNet concatenates one-hot encoded labels from all annotators, treating them as a union.
    • It enables direct end-to-end deep neural network training by maximizing the likelihood of this union.
    • A parametric transition matrix is utilized for training.

    Main Results:

    • The proposed method, UnionNet, demonstrates theoretical learning consistency.
    • Experimental results confirm the effectiveness and efficiency of UnionNet compared to existing approaches.
    • UnionNet successfully coordinates multiple annotators for improved data annotation.

    Conclusions:

    • UnionNet provides a theoretically sound and practically superior solution for crowdsourced data annotation.
    • The method enhances both the consistency and computational efficiency of deep learning models trained on crowdsourced data.
    • UnionNet represents a significant advancement in leveraging collective intelligence for machine learning tasks.