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    METHOD, APPARATUS, AND ELECTRONIC DEVICE FOR TRAINING NEURAL NETWORK MODEL
    3.
    发明申请
    METHOD, APPARATUS, AND ELECTRONIC DEVICE FOR TRAINING NEURAL NETWORK MODEL 有权

    公开(公告)号：US20210374474A1

    公开(公告)日：2021-12-02

    申请号：US17400029

    申请日：2021-08-11

    Applicant: Tencent Technology (Shenzhen) Company Limited

    Inventor： Rongbo SHEN ,  Kezhou YAN ,  Kuan TIAN ,  Cheng JIANG ,  Ke ZHOU

    IPC: G06K9/62 ,  G06N3/08

    Abstract: The present disclosure relates to a method for training a neural network model performed at an electronic device. The method includes: performing initial training by using a first training sample set to obtain an initial neural network model; performing a prediction on a second training sample set by using the initial neural network model to obtain a prediction result of each of training samples in the second training sample set; determining a plurality of preferred samples from the second training sample set based on the prediction results; adding the plurality of preferred samples that are annotated to the first training sample set to obtain an expanded first training sample set; updating training of the initial neural network model by using the expanded first training sample set to obtain an updated neural network model until a training ending condition is satisfied.

    MEDICAL IMAGE REGION SCREENING METHOD AND APPARATUS AND STORAGE MEDIUM
    8.
    发明申请
    MEDICAL IMAGE REGION SCREENING METHOD AND APPARATUS AND STORAGE MEDIUM 有权

    公开(公告)号：US20210343021A1

    公开(公告)日：2021-11-04

    申请号：US17367316

    申请日：2021-07-02

    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

    Inventor： Cheng JIANG ,  Kuan TIAN

    IPC: G06T7/11 ,  G06T5/00

    Abstract: A medical image region screening method and apparatus and a storage medium are provided. The method includes: obtaining a medical image of biological tissue, segmenting tissue regions of a plurality of tissue types from the medical image, selecting, from the tissue regions of the plurality of tissue types based on types of capturing positions of the medical image, a reserved region, obtaining a positional relationship between the reserved region and a predicted lesion region in the medical image; and screening for the predicted lesion region in the medical image based on the positional relationship, to obtain a target lesion region.

    METHOD AND APPARATUS FOR TRAINING CLASSIFICATION TASK MODEL, DEVICE, AND STORAGE MEDIUM
    9.
    发明申请
    METHOD AND APPARATUS FOR TRAINING CLASSIFICATION TASK MODEL, DEVICE, AND STORAGE MEDIUM 有权

    公开(公告)号：US20210319258A1

    公开(公告)日：2021-10-14

    申请号：US17355310

    申请日：2021-06-23

    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

    Inventor： Rong Bo SHEN ,  Ke ZHOU ,  Kuan TIAN ,  Ke Zhou YAN ,  Cheng JIANG

    IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04

    Abstract: Provided are an artificial intelligence (AI)-based method and apparatus for training a classification task model, a device, and a storage medium, which relate to the field of machine learning (ML) technologies. The method includes: training an initial feature extractor by using a first dataset to obtain a feature extractor, the first dataset being a class imbalanced dataset; constructing a generative adversarial network, the generative adversarial network including the feature extractor and an initial feature generator; training the generative adversarial network by using second class samples to obtain a feature generator; constructing a classification task model, the classification task model including the feature generator and the feature extractor; and training the classification task model by using the first dataset, the feature generator being configured to augment the second class samples in a feature space in a training process of the classification task model.

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