The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 09, 2024

Filed:

Dec. 27, 2021
Applicant:

Tsinghua University, Beijing, CN;

Inventors:

Gao Huang, Beijing, CN;

Shiji Song, Beijing, CN;

Chaoqun Du, Beijing, CN;

Assignee:

Tsinghua University, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/26 (2022.01); G06T 7/11 (2017.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/26 (2022.01); G06T 7/11 (2017.01); G06V 10/7715 (2022.01); G06V 10/7747 (2022.01); G06V 10/776 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10081 (2013.01); G06V 10/82 (2022.01); G06V 2201/031 (2022.01);
Abstract

An image processing method and apparatus and a storage medium, wherein the method particularly includes firstly acquiring an image-to-be-trained sample and a label segmentation image corresponding to the image-to-be-trained sample; inputting the image-to-be-trained sample into an image segmentation model to be trained, obtaining a first image feature of a last one output layer in the image segmentation model and a second image feature of a second last output layer when the image-to-be-trained sample is being extracted by using the image segmentation model, outputting the corresponding segmented-image samples; based on the label segmentation image and the segmented-image samples, calculating the model loss function, optimizing the model parameter, and generating the image segmentation model that has been optimized; and inputting an acquired image to be processed into the image segmentation model that has been optimized, and generating segmented images corresponding to the image to be processed.


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