公开(公告)号：US10819903B2

公开(公告)日：2020-10-27

申请号：US16261419

申请日：2019-01-29

Applicant: Olympus Corporation

Inventor： Yoshiyuki Fukuya ,  Kazuhiko Shimura ,  Hisashi Yoneyama ,  Zhen Li ,  Atsushi Kohashi ,  Dai Ito ,  Nobuyuki Shima ,  Yoichi Yoshida ,  Kazuhiko Osa ,  Osamu Nonaka

IPC: H04N5/232 ,  G06N5/04 ,  G10L15/22 ,  G06N3/04 ,  G06N3/08 ,  G10L17/00

Abstract: An imaging device, comprising an image sensor that images a shooting target and outputs image data, a memory that stores inference models for performing guidance display or automatic control, when shooting the shooting target, an inference engine that performs inference for the control of the guidance display or automatic control, using the inference model, and a controller that determines whether or not the inference model is suitable for shooting a shooting target that the user wants, and if it is determined that the inference model is not suitable for shooting, requests generation of an inference model that is suitable for a shooting target the user wants to an external learning device.

公开(公告)号：US10769497B2

公开(公告)日：2020-09-08

申请号：US16043057

申请日：2018-07-23

Applicant: Olympus Corporation

Inventor： Kazuhiro Haneda ,  Hisashi Yoneyama ,  Atsushi Kohashi ,  Zhen Li ,  Dai Ito ,  Yoichi Yoshida ,  Kazuhiko Osa ,  Osamu Nonaka

IPC: G06K9/00 ,  G06K9/62 ,  G06N3/08 ,  G06N20/10

Abstract: A learning device, comprising a reception circuit that receives requests indicating photographs the user likes from external device, a machine learning processor that extracts images that match the requests and that have received a given evaluation from a third party, from within an image database, performs machine learning using these images that have been extracted, and outputs an inference model, and a transmission circuit that transmits an inference model that has been output from the learning processor to the external device.

公开(公告)号：US20190325577A1

公开(公告)日：2019-10-24

申请号：US16460174

申请日：2019-07-02

Applicant: OLYMPUS CORPORATION

Inventor： Yoshioki Kaneko ,  Takeshi Otsuka ,  Zhen Li

IPC: G06T7/00 ,  G06T7/162 ,  G01N15/14

Abstract: An image processing device includes a processor including hardware. The processor is configured to: sequentially perform, on all at least two types of stains, an extraction process to extract a stained area due to a target stain from a single stain image of the target stain, starting from a stain having high specificity with regard to a target site; and sequentially perform a correction process, on all at least one type of second stain except for a first stain having the highest specificity among the at least two types of stains, to correct the single stain image by excluding stained areas of all stains having higher specificity than the target stain from the single stain image of the target stain, starting from the stain having the high specificity.

公开(公告)号：US10860890B2

公开(公告)日：2020-12-08

申请号：US16283710

申请日：2019-02-22

Applicant: Olympus Corporation

Inventor： Kazuhiro Haneda ,  Dai Ito ,  Zhen Li ,  Kazuhiko Osa ,  Osamu Nonaka

IPC: G06K9/62 ,  G06N20/00 ,  G06N5/04

Abstract: A learning management device comprising an inference engine that is input with image data and acquires output for performing guidance display to a user using an inference model that has been specifically learned, and a processor that confirms if there is a specified relationship between a trial input image and trial guidance display for this trial input image under conditions that have been assumed at the time of use, and that determines whether or not it is necessary to relearn the inference model that has been learned based on the result of this confirmation.

公开(公告)号：US20190197359A1

公开(公告)日：2019-06-27

申请号：US16043057

申请日：2018-07-23

Applicant: Olympus Corporation

Inventor： Kazuhiro HANEDA ,  Hisashi YONEYAMA ,  Atsushi Kohashi ,  Zhen Li ,  Dai Ito ,  Yoichi Yoshida ,  Kazuhiko Osa ,  Osamu NONAKA

IPC: G06K9/62 ,  G06N3/08

Abstract: A learning device, comprising a reception circuit that receives requests indicating photographs the user likes from external device, a machine learning processor that extracts images that match the requests and that have received a given evaluation from a third party, from within an image database, performs machine learning using these images that have been extracted, and outputs an inference model, and a transmission circuit that transmits an inference model that has been output from the learning processor to the external device.

公开(公告)号：US11037294B2

公开(公告)日：2021-06-15

申请号：US16460174

申请日：2019-07-02

Applicant: OLYMPUS CORPORATION

Inventor： Yoshioki Kaneko ,  Takeshi Otsuka ,  Zhen Li

IPC: G06K9/00 ,  G06T7/00 ,  G06T7/162 ,  G01N15/14 ,  G06T5/10

Abstract: An image processing device includes a processor including hardware. The processor is configured to: sequentially perform, on all at least two types of stains, an extraction process to extract a stained area due to a target stain from a single stain image of the target stain, starting from a stain having high specificity with regard to a target site; and sequentially perform a correction process, on all at least one type of second stain except for a first stain having the highest specificity among the at least two types of stains, to correct the single stain image by excluding stained areas of all stains having higher specificity than the target stain from the single stain image of the target stain, starting from the stain having the high specificity.

公开(公告)号：US11030482B2

公开(公告)日：2021-06-08

申请号：US16552542

申请日：2019-08-27

Applicant: OLYMPUS CORPORATION

Inventor： Toshikazu Hayashi ,  Zhen Li ,  Hisayuki Harada ,  Seiichiro Sakaguchi ,  Kazuhiko Osa ,  Osamu Nonaka

IPC: G06K9/62 ,  G06F3/14 ,  G06K9/48 ,  G06N3/08

Abstract: An annotation device, comprising: a display that performs sequential playback display of a plurality of images that may contain physical objects that are the subject of annotation, and a processor that acquires specific portions that have been designated within the images displayed on the display as annotation information, sets operation time or data amount for designating the specific portions, and at a point in time where designation of the specific portions has been completed for the operation time, a time based on data amount, or data amount, that have been set, requests learning to an inference engine that creates an inference model by learning, using annotation information that has been acquired up to the time of completion as training data representing a relationship between the physical object and the specific portions.