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:
May. 09, 2023

Filed:

Jul. 01, 2021
Applicant:

Molecular Devices, Llc, San Jose, CA (US);

Inventors:

Avrum Cohen, San Jose, CA (US);

Dihui Hong, San Jose, CA (US);

Stephen Rhein, San Jose, CA (US);

Assignee:

MOLECULAR DEVICES, LLC, San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/69 (2022.01); G06K 9/62 (2022.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06V 20/695 (2022.01); G06K 9/6254 (2013.01); G06K 9/6256 (2013.01); G06T 7/0014 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01);
Abstract

A system and method for analyzing images using programmable device is disclosed. A sequencer operating on the non-transitory programmable device applies the first image analysis step to the first image to develop annotated training data. Specifications of the first image and the first image analysis step are developed using a graphical user interface operating on a computer. In addition, a machine learning system trainer operating on the programmable device trains an untrained machine learning system to develop a trained machine learning system. When the trained machine learning system is presented with the first image as an input, the trained machine learning system develops a prediction of the annotated training data. In addition, the sequencer analyzes a second image by undertaking a workflow, wherein the workflow is received from the computer and is specified using the graphical user interface and comprises a second image analysis step that that specifies operating the trained machine learning system.


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