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:
Jun. 02, 2026

Filed:

Jul. 25, 2023
Applicant:

Dell Products L.p., Round Rock, TX (US);

Inventors:

Zijia Wang, Weifang, CN;

Zhisong Liu, Shenzhen, CN;

Zhen Jia, Shanghai, CN;

Assignee:

Dell Products L.P., Round Rock, TX (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/774 (2022.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 20/70 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/774 (2022.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 20/70 (2022.01); G06V 10/82 (2022.01);
Abstract

Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for generating image samples. The method includes processing a group of image samples using a class capsule network model, and obtaining a group of distilled samples, a feature distribution of the group of distilled samples indicating a feature distribution of the group of image samples; and determining a soft label of each distilled sample in the group of distilled samples on the basis of a label of the group of image samples, the soft label representing a probability that the distilled sample belongs to each of a plurality of classes. As such, class capsules in a trained capsule network model are extracted as distilled samples, and soft labels are assigned to the distilled samples on the basis of original image samples, so that the extracted distilled samples can be ensured to have high explainability.


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