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. 03, 2023

Filed:

Oct. 28, 2022
Applicant:

Seadronix Corp., Ulsan, KR;

Inventors:

Byeol Teo Park, Daejeon, KR;

Han Keun Kim, Hwaseong-si, KR;

Dong Hoon Kim, Daejeon, KR;

Assignee:

Seadronix Corp., Ulsan, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/00 (2022.01); G08G 3/02 (2006.01); G06T 7/50 (2017.01); G06T 7/70 (2017.01); G06N 3/08 (2023.01); B63B 79/15 (2020.01); G06F 18/21 (2023.01); G06F 18/2431 (2023.01); G06T 7/11 (2017.01);
U.S. Cl.
CPC ...
G06V 20/00 (2022.01); B63B 79/15 (2020.01); G06F 18/21 (2023.01); G06F 18/2431 (2023.01); G06N 3/08 (2013.01); G06T 7/50 (2017.01); G06T 7/70 (2017.01); G08G 3/02 (2013.01); G06T 7/11 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30252 (2013.01);
Abstract

A method for situation awareness is provided. The method comprises: preparing a neural network trained by a learning set, wherein the learning set includes a plurality of maritime images and maritime information including object type information which includes a first type index for a vessel, a second type index for a water surface and a third type index for a ground surface, and distance level information which includes a first level index indicating that a distance is undefined, a second level index indicating a first distance range and a third level index indicating a second distance range greater than the first distance range; obtaining a target maritime image generated from a camera; and determining a distance of a target vessel based on the distance level index of the maritime information being outputted from the neural network which receives the target maritime image and having the first type index.


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