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:
Oct. 27, 2020

Filed:

Oct. 11, 2018
Applicants:

Disney Enterprises, Inc., Burbank, CA (US);

Eth Zurich, Zurich, CH;

Inventors:

Thomas Muller, Rheinfelden, DE;

Brian McWilliams, Zurich, CH;

Fabrice Pierre Armand Rousselle, Ostermundigen, CH;

Jan Novak, Zurich, CH;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 7/00 (2006.01); G06T 15/50 (2011.01); G06N 3/04 (2006.01); G06T 15/06 (2011.01); G06N 3/08 (2006.01); G06T 15/00 (2011.01); G06N 3/10 (2006.01);
U.S. Cl.
CPC ...
G06T 15/506 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 3/10 (2013.01); G06T 15/005 (2013.01); G06T 15/06 (2013.01);
Abstract

According to one implementation, a system includes a computing platform having a hardware processor and a system memory storing a software code including multiple artificial neural networks (ANNs). The hardware processor executes the software code to partition a multi-dimensional input vector into a first vector data and a second vector data, and to transform the second vector data using a first piecewise-polynomial transformation parameterized by one of the ANNs, based on the first vector data, to produce a transformed second vector data. The hardware processor further executes the software code to transform the first vector data using a second piecewise-polynomial transformation parameterized by another of the ANNs, based on the transformed second vector data, to produce a transformed first vector data, and to determine a multi-dimensional output vector based on an output from the plurality of ANNs.


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