Patent ID: 11900647
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. The image classification method according to claim 1, wherein:
the first image feature includes a first target image feature and a second target image feature, the first target image feature is obtained by performing convolution processing on the target image by using a first neural network including at least one convolutional layer, and the second target image feature is obtained by performing convolution processing on the target image by using a second neural network;
the second image feature includes a first target reference image feature and a second target reference image feature, wherein the first target reference image feature is obtained by performing convolution processing on the reference image by using the first neural network including the at least one convolutional layer, and the second target reference image feature is obtained by performing convolution processing on the reference image by using the second neural network; and
the first neural network is obtained by performing training by using a first training set, the second neural network is obtained by performing training by using a second training set, and proportions of positive samples to negative samples in training images included in the first training set and the second training set are different.