公开(公告)号：US20210390319A1

公开(公告)日：2021-12-16

申请号：US17344629

申请日：2021-06-10

Applicant: SHANDONG UNIVERSITY

Inventor： Yang YANG ,  Chenguan LI ,  Peng XU ,  Yunxia LIU ,  Man GUO ,  Yujun LI

IPC: G06K9/00

Abstract: A scene change method and system combining instance segmentation and cycle generative adversarial networks are provided. The method includes: processing a video of a target scene and then inputting the video into an instance segmentation network to obtain segmented scene components, that is, obtain mask cut images of the target scene; and processing targets in the mask cut images of the target scene by using cycle generative adversarial networks according to the requirements of temporal attributes to generate data in a style-migrated state, and generating style-migrated targets with unfixed spatial attributes into a style-migrated static scene according to a specific spatial trajectory to achieve a scene change effect.

公开(公告)号：US20240203599A1

公开(公告)日：2024-06-20

申请号：US17910556

申请日：2021-07-16

Applicant: SHANDONG UNIVERSITY

Inventor： Zhi LIU ,  Yujun LI ,  Xifeng HU ,  Weifeng HU

IPC: G16H50/30 ,  G16H10/60

CPC classification number: G16H50/30 ,  G16H10/60

Abstract: A method and system of predicting disease risk based on multimodal fusion, the method comprises: obtaining electronic health record (EHR) data of the patient, inputting the EHR data into the disease risk prediction model to obtain the disease risk prediction result; and outputting the disease risk prediction result; wherein, the disease risk prediction model performing steps of: identifying the EHR data as the structured data and the unstructured data; performing the data cleaning on the structure data and the unstructured data; extracting structured data features and unstructured data features; extracting fusion features, wherein the fusion features are features fusing the unstructured data feature and the structured data feature; and, performing the disease risk prediction on the fusion features.