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:
Jan. 24, 2023

Filed:

Feb. 23, 2021
Applicants:

Owkin Inc., New York, NY (US);

Owkin France Sas, Paris, FR;

Inventors:

Pierre Courtiol, Paris, FR;

Olivier Moindrot, Paris, FR;

Charles Maussion, Paris, FR;

Charlie Saillard, Paris, FR;

Benoit Schmauch, Paris, FR;

Gilles Wainrib, Pantin, FR;

Assignees:

OWKIN, INC., New York, NY (US);

OWKIN FRANCE SAS, Paris, FR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/69 (2022.01); G06T 7/194 (2017.01); G06T 7/11 (2017.01); G06K 9/62 (2022.01); G06T 7/00 (2017.01); G06V 10/50 (2022.01); G06V 10/82 (2022.01); G06V 10/764 (2022.01); G06N 3/04 (2006.01); G06V 10/32 (2022.01);
U.S. Cl.
CPC ...
G06V 20/695 (2022.01); G06K 9/627 (2013.01); G06K 9/6218 (2013.01); G06K 9/6256 (2013.01); G06K 9/6261 (2013.01); G06K 9/6262 (2013.01); G06N 3/04 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 7/194 (2017.01); G06V 10/32 (2022.01); G06V 10/50 (2022.01); G06V 10/82 (2022.01); G06V 20/698 (2022.01); G06T 2207/10056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01); G06V 10/764 (2022.01);
Abstract

A method and apparatus of a device that classifies an image is described. In an exemplary embodiment, the device segments the image into a region of interest that includes information useful for classification and a background region by applying a first convolutional neural network. In addition, the device tiles the region of interest into a set of tiles. For each tile, the device extracts a feature vector of that tile by applying a second convolutional neural network, where the features of the feature vectors represent local descriptors of the tile. Furthermore, the device processes the extracted feature vectors of the set of tiles to classify the image.


Find Patent Forward Citations

Loading…