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:
Aug. 20, 2024

Filed:

Dec. 15, 2021
Applicant:

Intelligent Fusion Technology, Inc., Germantown, MD (US);

Inventors:

Qi Zhao, Germantown, MD (US);

Huong Ngoc Dang, Germantown, MD (US);

Yi Li, Germantown, MD (US);

Xin Tian, Germantown, MD (US);

Nichole Sullivan, Germantown, MD (US);

Genshe Chen, Germantown, MD (US);

Khanh Pham, Kirtland AFB, NM (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/94 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01); G06V 10/96 (2022.01);
U.S. Cl.
CPC ...
G06V 10/95 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01); G06V 10/96 (2022.01);
Abstract

A system includes: a named data networking (NDN) based Spark distributed computing network including a Spark distributed computing network including a master computer node and a plurality of slave computer nodes, and a named data networking (NDN) protocol installed on the Spark distributed computing network, and a coded distributed computing (CDC) target recognition model deployed on the NDN-based Spark distributed computing network. The NDN-based Spark distributed computing network is configured to: receive one or more batches of input images; generate a parity image from each batch of the input images; predict a label for each image of the batch of the input images; process the generated parity image; upon a label prediction of one image of the batch of the input images being unavailable, reconstruct the unavailable label prediction; and classify labels for the input images.


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