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公开(公告)号：US20220254177A1
公开(公告)日：2022-08-11
申请号：US17596279
申请日：2019-06-07
Applicant: Leica Microsystems CMS GmbH
Inventor： Constantin KAPPEL
IPC: G06V20/69 , G06V10/82 , G06V10/774 , G06V10/44
Abstract: A system (100) comprising one or more processors (110) and one or more storage devices (120) is configured to obtain biology-related image-based input data (107) and generate a high-dimensional representation of the biology-related image-based input data (107) by a trained visual recognition machine-learning algorithm executed by the one or more processors (110). The high-dimensional representation comprises at least 3 entries each having a different value. Further, the system is configured to at least one of store the high-dimensional representation of the biology-related image-based input data (107) together with the biology-related image-based input data (107) by the one or more storage devices (120) or output biology-related language-based output data (109) corresponding to the high-dimensional representation.
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公开(公告)号：US20220246244A1
公开(公告)日：2022-08-04
申请号：US17596290
申请日：2019-06-07
Applicant: Leica Microsystems CMS GmbH
Inventor： Constantin KAPPEL
Abstract: A system (100) comprises one or more processors (110) and one or more storage devices (120), wherein the system (100) is configured to generate a first high-dimensional representation of the biology-related language-based input training data (102) by a language recognition machine-learning algorithm executed by the one or more processors (110). Further, the system (100) is configured to generate biology-related language-based output training data based on the first high-dimensional representation by the language recognition machine-learning algorithm and adjust the language recognition machine-learning algorithm based on a comparison of the biology-related language-based input training data (102) and the biolo-gy-related language-based output training data. Additionally. the system (100) is configured to generate a second high-dimensional representation of the biology-related image-based input training data (104) by a visual recognition machine-learning algorithm executed by the one or more processors (110) and adjust the visual recognition machine-learning algorithm based on a comparison of the first high-dimensional representation and the second high-dimensional representation.
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公开(公告)号：US20210342569A1
公开(公告)日：2021-11-04
申请号：US17285478
申请日：2019-09-25
Applicant: LEICA MICROSYSTEMS CMS GMBH
Inventor： Frank SIECKMANN , Constantin KAPPEL
Abstract: An apparatus for optimizing workflows of one or more microscopes and/or microscope systems includes one or more processors and one or more computer-readable storage media. The one or more computer-readable storage media have stored therein computer-executable instructions, which, when executed by the one or more processors cause execution of the following steps: implementing, by one or more components of the one or more microscopes and/or microscope systems, a workflow comprising a capture of first data; applying one or more trained models to the captured first data; and making at least one decision in relation to the workflow based on the application of the one or more trained models to the captured first data.
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