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公开(公告)号:US20220114776A1
公开(公告)日:2022-04-14
申请号:US17280142
申请日:2020-07-03
Inventor: Xianglong XU , Jianfeng ZHU , Jiahua CUI , Jing XIANG , Hongtao LI , Chen HAN , Shufei LIN , Ying SU , Shicao LI , Huiqin LI , Xiaochu GAN , Fei GAO , Jiale YANG , Xueyun MA , Guohong LI
IPC: G06T11/60 , G06F40/279 , G06V10/74 , G06F40/30 , G06V40/16
Abstract: Provided are an emoticon package generation method and apparatus, a device and a medium which relate to the field of graphic processing and in particular to Internet technologies. The specific implementation solution is: determining at least one of associated text of an emoticon picture or a similar emoticon package of an emoticon picture, where the associated text of the emoticon picture includes at least one of main part information, scenario information, emotion information, action information or connotation information; determining target matching text from the at least one of the associated text of the emoticon picture or associated text of the similar emoticon package; and superimposing the target matching text on the emoticon picture to generate a new emoticon package.
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2.
公开(公告)号:US20210390682A1
公开(公告)日:2021-12-16
申请号:US17116597
申请日:2020-12-09
Inventor: Shufei LIN , Jianfeng ZHU , Pengcheng YUAN , Bin ZHANG , Shumin HAN , Yingbo XU , Yuan FENG , Ying XIN , Xiaodi WANG , Jingwei LIU , Shilei WEN , Hongwu ZHANG , Errui DING
Abstract: A method for detecting a surface defect, a method for training model, an apparatus, a device, and a medium, are provided. The method includes: inputting a surface image of the article for detection into a defect detection model to perform a defect detection, and acquiring a defect detection result output by the defect detection model; inputting a surface image of a defective article determined to be defective into an image discrimination model based on the defect detection result to determine whether the surface image of the defective article is defective, wherein the image discrimination model is a trained generative adversarial networks model, and the generative adversarial networks model is obtained by training using a surface image of a defect-free good article; and adjusting the defect detection result of the surface image of the defective article according to a determination result of the image discrimination model.
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