公开(公告)号：US20250117710A1

公开(公告)日：2025-04-10

申请号：US18985365

申请日：2024-12-18

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

Inventor： Mingxiu ZHANG ,  Yahui WANG ,  Fangxin SHANG ,  Jun CHEN ,  Haifeng HUANG

IPC: G06N20/00 ,  G10L25/27

Abstract: Provided is a method of deploying a multimodal large model, an electronic device and a storage medium, relating to field of artificial intelligence technology, and in particular, to fields of deep learning and model deployment. The method includes: splitting a first multimodal large model into a visual part and a linguistic part; determining a first static graph model corresponding to the visual part and a second static graph model corresponding to the linguistic part; and deploying the first multimodal large model based on the first static graph model and the second static graph model.

公开(公告)号：US20210192728A1

公开(公告)日：2021-06-24

申请号：US17097632

申请日：2020-11-13

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Fangxin SHANG ,  Yehui YANG ,  Lei WANG ,  Yanwu XU

IPC: G06T7/00 ,  A61B3/12

Abstract: The present application discloses an image processing method, an apparatus, an electronic device and a storage medium. A specific implementation is: acquiring an image to be processed; acquiring a grading array according to the image to be processed and a grading network model, where the grading network model is a model pre-trained according to mixed samples, the number of elements contained in the grading array is C−1, C is the number of lesion grades, C lesion grades include one lesion grade without lesion and C−1 lesion grades with lesion, and a kth element in the grading array is a probability of a lesion grade corresponding to the image to be processed being greater than or equal to a kth lesion grade, where 1≤k≤C−1, and k is an integer; determining the lesion grade corresponding to the image to be processed according to the grading array.