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:
Dec. 31, 2019

Filed:

Oct. 12, 2017
Applicant:

Lawrence Livermore National Security, Llc, Livermore, CA (US);

Inventors:

Peer-Timo Bremer, Livermore, CA (US);

Hyojin Kim, Livermore, CA (US);

Jayaraman J. Thiagarajan, Livermore, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06K 9/20 (2006.01); G06K 9/46 (2006.01); G06T 7/143 (2017.01); G06N 7/00 (2006.01); G06T 7/11 (2017.01);
U.S. Cl.
CPC ...
G06K 9/6259 (2013.01); G06K 9/2054 (2013.01); G06K 9/46 (2013.01); G06K 9/6269 (2013.01); G06K 9/6277 (2013.01); G06N 7/005 (2013.01); G06T 7/11 (2017.01); G06T 7/143 (2017.01); G06T 2200/04 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20076 (2013.01); G06T 2210/12 (2013.01);
Abstract

A system for identifying objects in an image is provided. The system identifies segments of an image that may contain objects. For each segment, the system generates a segment score by inputting to a multi-scale neural network windows of multiple scales that include the segment that have been resampled to a fixed window size. A multi-scale neural network includes a feature extracting convolutional neural network ('feCNN') for each scale and a classifier that inputs each feature of each feCNN. The segment score indicates whether the segment contains an object. The system generates a pixel score for pixels of the image. The pixel score for a pixel indicates that that pixel is within an object based on the segment scores of segments that contain that pixel. The system then identifies the object based on the pixel scores of neighboring pixels.


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