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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 10599978 B1

PDFFull Text
Date of Patent:
Mar. 24, 2020

Filed:

Nov. 03, 2017

Weighted cascading convolutional neural networks

Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Taro Sekiyama, Urayasu, JP;

Masaharu Sakamoto, Yokohama, JP;

Hiroki Nakano, Otsu, JP;

Kun Zhao, Funabashi, JP;

Assignee:

International Business Machines Corporation, Armonk, NY (US);

Attorney:

Stosch Sabo

Primary Examiner:

Tsung Yin Tsai

Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06N 3/0454 (2013.01); G06K 9/6217 (2013.01); G06K 9/6267 (2013.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

A cascading convolutional neural network (CCNN) comprising a plurality of convolutional neural networks (CNNs) that are trained by weighting training data based on loss values of each training datum between CNNs of the CCN. The CCNN can receiving an input image from plurality of images, classify the input image using the CCNN, and present a classification of the input image.

Find Patent Forward Citations

Sekiyama, Taro. (2020). Weighted cascading convolutional neural networks (U.S. Patent No. 10599978). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/10599978

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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