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. 13, 2023

Filed:

Feb. 24, 2017
Applicant:

Sri International, Menlo Park, CA (US);

Inventors:

Sek Meng Chai, Princeton, NJ (US);

David Zhang, Belle Mead, NJ (US);

Mohamed Amer, Brooklyn, NY (US);

Timothy J. Shields, Houston, TX (US);

Aswin Nadamuni Raghavan, Princeton, NJ (US);

Assignee:

SRI International, Menlo Park, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/04 (2023.01); G06N 3/084 (2023.01); G06V 10/52 (2022.01); G06F 18/00 (2023.01); G06F 18/21 (2023.01); G06F 18/24 (2023.01); G06F 18/2413 (2023.01); G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06N 3/082 (2023.01); G06N 3/086 (2023.01); G06N 3/044 (2023.01);
U.S. Cl.
CPC ...
G06N 3/084 (2013.01); G06F 18/00 (2023.01); G06F 18/21 (2023.01); G06F 18/24 (2023.01); G06F 18/2413 (2023.01); G06N 3/045 (2023.01); G06V 10/52 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06N 3/044 (2023.01); G06N 3/082 (2013.01); G06N 3/086 (2013.01);
Abstract

Artificial neural network systems involve the receipt by a computing device of input data that defines a pattern to be recognized (such as faces, handwriting, and voices). The computing device may then decompose the input data into a first subband and a second subband, wherein the first and second subbands include different characterizing features of the pattern in the input data. The first and second subbands may then be fed into first and second neural networks being trained to recognize the pattern. Reductions in power expenditure, memory usage, and time taken, for example, allow resource-limited computing devices to perform functions they otherwise could not.


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