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:
Apr. 16, 2024

Filed:

Jun. 07, 2019
Applicant:

Leica Microsystems Cms Gmbh, Wetzlar, DE;

Inventor:

Constantin Kappel, Schriesheim, DE;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); G06F 16/33 (2019.01); G06F 16/583 (2019.01); G06F 18/22 (2023.01); G06F 40/40 (2020.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/082 (2023.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01);
U.S. Cl.
CPC ...
G06F 16/3344 (2019.01); G06F 16/583 (2019.01); G06F 18/22 (2023.01); G06F 40/40 (2020.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/082 (2013.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01);
Abstract

Embodiments relate to a system () comprising one or more processors () and one or more storage devices (). The system () is configured to receive biology-related language-based search data () and generate a first high-dimensional representation of the biology-related language-based search data () by a trained language recognition ma-chine-learning algorithm executed by the one or more processors (). The first high-dimensional representation comprises at least 3 entries each having a different value. Further, the system is configured to obtain a plurality of second high-dimensional representations () of a plurality of biology-related image-based input data sets or of a plurality of biology-related language-based input data sets and compare the first high-dimensional representation with each second high-dimensional representation of the plurality of second high-dimensional representations ().


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