Data labeling model training method, electronic device and storage medium
AssigneeHon Hai Precision Industry Co., Ltd.
InventorsTung-Tso TSAI, Chin-Pin KUO, Wan-Jhen LEE, Guo-Chin SUN
Life of this patent
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Abstract
A data labeling model training method, an electronic device employing the method, and a storage medium are provided. The method acquires medical image data. An improved quality of the medical image data to be used for training the data labeling model is obtained by filtering the medical data, so as to enable training with higher-quality training material. The data labeling model is used to label medical data with improved efficiency and accuracy.
Claims20
A data labeling model training method, the method comprising:
- acquiring medical image data;
- filtering the medical image data to obtain filtered data;
- classifying the filtered data to obtain data classified into different categories;
- acquiring labeling information corresponding to the classified data;
- forming labeling data according to the category of the classified data, the classified data, and the labeling information;
- training the labeling data and obtaining a data labeling model.
An electronic device comprising a storage medium and a processor, the storage medium stores at least one computer-readable instruction, and the processor executes the at least one computer-readable instruction to implement to:
- acquire medical image data;
- filter the medical image data to obtain filtered data;
- classify the filtered data to obtain data classified into different categories;
- acquire labeling information corresponding to the classified data;
- form labeling data according to the category of the classified data, the classified data, and the labeling information;
- train the labeling data and obtaining a data labeling model.
A non-transitory storage medium having stored thereon at least one computer-readable instruction that, when the at least one computer-readable instruction are executed by a processor to implement the following steps:
- acquiring medical image data;
- filtering the medical image data to obtain filtered data;
- classifying the filtered data to obtain data classified into different categories;
- acquiring labeling information corresponding to the classified data;
- forming labeling data according to the category of the classified data, the classified data, and the labeling information;
- training the labeling data and obtaining a data labeling model.
Dependencies are inferred from the claim text.