US 11,928,563 B2
Model training, image processing method, device, storage medium, and program product
Xingjian Li, Beijing (CN); Haoyi Xiong, Beijing (CN); and Dejing Dou, Beijing (CN)
Assigned to Beijing Baidu Netcom Science Technology Co., Ltd., Beijing (CN)
Filed by Beijing Baidu Netcom Science Technology Co., Ltd., Beijing (CN)
Filed on Jun. 23, 2021, as Appl. No. 17/355,347.
Claims priority of application No. 202011510141.X (CN), filed on Dec. 18, 2020.
Prior Publication US 2021/0319262 A1, Oct. 14, 2021
Int. Cl. G06N 20/00 (2019.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 18/24 (2023.01); G06F 18/25 (2023.01); G06N 5/04 (2023.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 10/84 (2022.01)
CPC G06N 20/00 (2019.01) [G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 18/24 (2023.01); G06F 18/251 (2023.01); G06N 5/04 (2013.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 10/84 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A model training method, comprising:
acquiring target image data for learning a target task, and source image data for learning a preset task;
determining auxiliary image data in the source image data according to the target image data;
determining a to-be-trained model according to a trained preset model corresponding to the preset task and a preset classification network;
determining fused image data according to the target image data and the auxiliary image data, and
training the to-be-trained model with the fused image data, to obtain a target model for executing the target task.