Patent ID: 11961609
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. The method according to claim 7, wherein the image classification model is trained by:
(a) obtaining a first training sample set, the first training sample set comprising at least one 3D sample image, the 3D sample image being annotated with an expected classification result;
(b) inputting the 3D sample image into an initial neural network model, to obtain an actual classification result;
(c) calculating a loss function value according to the expected classification result and the actual classification result;
(d) adjusting parameters in the initial neural network model based on the loss function value not meeting a preset condition, and performing operations (a)-(c) with the adjusted parameters; and
(e) stopping training of the image classification model based on the loss function value meeting the preset condition, to obtain the image classification model.