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:
Aug. 06, 2024

Filed:

Oct. 14, 2021
Applicant:

Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;

Inventors:

Yifan Hu, Shenzhen, CN;

Yuexiang Li, Shenzhen, CN;

Yefeng Zheng, Shenzhen, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 20/70 (2022.01); A61B 6/00 (2024.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06N 3/0455 (2023.01); G06T 7/10 (2017.01); G06T 7/143 (2017.01); G06T 9/00 (2006.01); G06V 20/69 (2022.01);
U.S. Cl.
CPC ...
G06F 18/2155 (2023.01); A61B 6/5294 (2013.01); G06F 18/2178 (2023.01); G06N 3/0455 (2023.01); G06T 7/10 (2017.01); G06T 7/143 (2017.01); G06T 9/002 (2013.01); G06V 20/695 (2022.01); G06V 20/70 (2022.01); G06T 2207/20112 (2013.01); G06T 2207/30004 (2013.01); G06T 2219/004 (2013.01);
Abstract

A method for determining a target image to be labeled includes: obtaining an original image and an autoencoder (AE) set, the original image being an image having not been labeled, the AE set including N AEs; obtaining an encoded image set corresponding to the original image by using the AE set, the encoded image set including N encoded images, the encoded images being corresponding to the AEs; obtaining the encoded image set and a segmentation result set corresponding to the original image by using an image segmentation network, the image segmentation network including M image segmentation sub-networks, and the segmentation result set including [(N+1)*M] segmentation results; determining labeling uncertainty corresponding to the original image according to the segmentation result set; and determining whether the original image is a target image according to the labeling uncertainty.


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