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. 06, 2015

Filed:

Sep. 13, 2013
Applicant:

Los Alamos National Security, Llc, Los Alamos, NM (US);

Inventors:

Steven P. Brumby, Santa Fe, NM (US);

Luis Bettencourt, Los Alamos, NM (US);

Garrett T. Kenyon, Santa Fe, NM (US);

Rick Chartrand, Los Alamos, NM (US);

Brendt Wohlberg, Los Alamos, NM (US);

Assignee:

Los Alamos National Security, LLC, Los Alamos, NM (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6221 (2013.01); G06K 9/6244 (2013.01); G06K 2009/4695 (2013.01);
Abstract

Approaches for deciding what individuals in a population of visual system 'neurons' are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.


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