Patent ID: 11967414
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 3:
4. The method according to claim 1, wherein the preset image recognition model is generated by:
obtaining a training image sample set, the training image sample set comprising at least one strong-label training image sample, the strong-label training image sample being an image sample having strong-label information, and the strong-label information comprising at least annotation information of a lesion category and a lesion position in the image sample;
extracting image feature information of each image sample in the training image sample set;
marking image feature information belonging to each preset lesion category based on the image feature information of the image sample and corresponding strong-label information; and
training an image recognition model according to a mark result until a strong supervision objective function of the image recognition model converges, to obtain the preset image recognition model, the strong supervision objective function being a loss function of a recognized lesion category and a lesion category in the strong-label information.