公开(公告)号：US20230244932A1

公开(公告)日：2023-08-03

申请号：US18076501

申请日：2022-12-07

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Ji LIU ,  Qilong LI ,  Yu LI ,  Xingjian LI ,  Yifan SUN ,  Dejing DOU

IPC: G06N3/08 ,  G06V10/82

CPC classification number: G06N3/08 ,  G06V10/82

Abstract: Provided are an image occlusion method, a model training method, a device, and a storage medium, which relate to the technical field of artificial intelligence, in particular, to the field of computer vision technologies and deep learning, and may be applied to image recognition, model training and other scenarios. The specific implementation solution is as follows: generating a candidate occlusion region according to an occlusion parameter; according to the candidate occlusion region, occluding an image to be processed to obtain a candidate occlusion image; determining a target occlusion region from the candidate occlusion region according to visual security and data availability of the candidate occlusion image; and according to the target occlusion region, occluding the image to be processed to obtain a target occlusion image. In this manner, the image to be processed is desensitized while the accuracy of target recognition is ensured.

公开(公告)号：US20240273297A1

公开(公告)日：2024-08-15

申请号：US18642593

申请日：2024-04-22

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Yu LI ,  Jiawei ZHENG ,  Xinjiang LU ,  Hongwei XIE ,  Xuejiao LIN ,  Jingbo ZHOU

IPC: G06F40/295

CPC classification number: G06F40/295

Abstract: An entity recognition method, a model training method, an electronic device, and a medium, which relate to fields of artificial intelligence, information acquiring technologies. The entity recognition method includes: extracting specified entities from a text in a source file of a webpage to be recognized, and acquiring a text encoding result for each specified entity; determining a text block formed by each specified entity in the webpage, and encoding a relative layout information between each two text blocks, to obtain a position encoding result; constructing a triple by the position encoding result for each two text blocks and the text encoding results for respective specified entities of the two text blocks; and performing a graph convolution on each triple to obtain a relation recognition result for the webpage to be recognized, where the relation recognition result indicates whether an association exists between each two text blocks in the webpage.