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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.

Patent No.:

US 12748975 B1

PDFFull Text
Date of Patent:
Sep. 29, 2026

Filed:

Dec. 29, 2022

Data feature extraction method and related apparatus

Applicant:

Huawei Technologies Co., Ltd., Shenzhen, CN;

Inventors:

Kai Han, Beijing, CN;

Yunhe Wang, Beijing, CN;

Chunjing Xu, Shenzhen, CN;

Assignee:

Huawei Technologies Co., Ltd., Shenzhen, CN;

Attorney:

Leydig, Voit & Mayer, Ltd.

Primary Examiner:

Quoc A Tran

Int. Cl.
CPC ...
G06N 3/084 (2023.01); G06F 7/544 (2006.01); G06F 18/21 (2023.01); G06N 3/045 (2023.01); G06N 3/0464 (2023.01); G06N 3/08 (2023.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06N 3/084 (2013.01); G06N 3/0464 (2023.01); B01J 2219/00216 (2013.01); G06F 7/5443 (2013.01); G06F 18/217 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
Abstract

A data feature extraction method and apparatus in the field of artificial intelligence are provided. An addition convolution operation is performed to extract a target feature in quantized data based on quantized feature extraction parameters, that is, to calculate a sum of absolute values of differences between the quantized feature extraction parameters and the quantized data, to obtain the target feature based on the sum. In addition, feature extraction parameters and data are quantized by using a same quantization parameter. According to this application, a storage resource is saved, a computing resource is saved, thereby reducing a limitation on an application of artificial intelligence to a resource-limited device. Further, when the extracted feature data is dequantized, the feature data may be dequantized based on the quantization parameters.

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