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公开(公告)号：US11417089B2
公开(公告)日：2022-08-16
申请号：US16494117
申请日：2018-02-16
Applicant: NEC Corporation
Inventor： Kousuke Ishida , Hajime Ishikawa , Shinji Oominato , Shunsuke Akimoto , Masami Sakaguchi , Shintaro Matsumoto
IPC: G06V20/00 , G06V20/10 , G06K9/62 , G06V30/194
Abstract: A vegetation index calculation apparatus (10) is provided with a learning model generation unit (11) that generates a learning model, by using an image of a crop targeted for calculation of a vegetation index and an image of plants other than the crop to learn a feature amount of the image of the crop, an image acquisition unit (12) that acquires an aerial image of a target region where the crop is being grown, a specification unit (13) that applies the aerial image acquired by the image acquisition unit (12) to the learning model generated by the learning model generation unit (11), and specifies the image of the crop in the aerial image acquired by the image acquisition unit (12), and a vegetation index calculation unit (14) that calculates the vegetation index of the crop, using the image of the crop specified by the specification unit (13).
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2.发明授权公开(公告)号：US11461884B2
公开(公告)日：2022-10-04
申请号：US16496644
申请日：2018-03-23
Applicant: NEC Corporation
Inventor： Kousuke Ishida , Hajime Ishikawa , Shinji Oominato , Shunsuke Akimoto , Shintaro Matsumoto , Masami Sakaguchi
Abstract: A field management apparatus 10 is provided with a learning model generation unit 11 that generates a learning model 15, to learn feature amounts of the image of the phenomenon that results from the fault in the field equipment, an image acquisition unit 12 that acquires an aerial image of a target region, an image specification unit 13 that applies the aerial image to the learning model 15, and specifies an image of the phenomenon that results from the fault in the field equipment in the aerial image, and a fault location specification unit 14 that specifies a fault location of the field equipment in the target region, based on the image of the phenomenon that results from the fault in the field equipment.
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Patent Agency Ranking
3.发明公开公开(公告)号：US20230377369A1
公开(公告)日：2023-11-23
申请号：US18030692
申请日：2020-10-12
Applicant: NEC Corporation
Inventor： Shin NORIEDA , Yoshiyuki Tanaka , Shogo Akasaki , Haruki Yokota , Masami Sakaguchi
CPC classification number: G06V40/174 , G06V40/172 , G06T7/11 , G06T2207/30201
Abstract: An analysis apparatus comprises at least one memory storing instructions, and at least one processor configured to execute the instructions to comprises at least one memory storing instructions, and at least one processor configured to execute the instructions to acquire emotion data from an emotion data generation apparatus that generates emotion data from face image data of a meeting participant in an online meeting, generate analysis data for the meeting on the basis of the emotion data, acquire meeting data including attribute data of the meeting, store message data in which a pattern of a message to be presented to a user is associated with the meeting data, select the message on the basis of the analysis data and the message data, and store an analysis result including the selected message in a storage unit in an outputtable manner.
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4.发明公开公开(公告)号：US20230351806A1
公开(公告)日：2023-11-02
申请号：US18030146
申请日：2020-10-12
Applicant: NEC Corporation
Inventor： Shin Norieda , Yoshiyuki Tanaka , Shogo Akasaki , Haruki Yokota , Masami Sakaguchi
CPC classification number: G06V40/174 , G06V20/50
Abstract: An analysis apparatus sequentially acquires emotion data generated for each first period based on face image data of participants during an online meeting. The analysis apparatus generates analysis data indicating one analysis value regarding an evaluation for a second period in an ongoing online meeting based on emotion data including at least the latest data. The analysis apparatus sequentially outputs the generated analysis data.
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公开(公告)号：US11348272B2
公开(公告)日：2022-05-31
申请号：US16496229
申请日：2018-02-22
Applicant: NEC Corporation
Inventor： Kousuke Ishida , Hajime Ishikawa , Shinji Oominato , Shunsuke Akimoto , Masami Sakaguchi , Shintaro Matsumoto
Abstract: A vegetation index calculation apparatus (10) is provided with a specification unit (11) that collates height distribution data indicating a distribution of the height of plants that exist in a target region with predicted height data of a crop targeted for calculation of a vegetation index, and specifies a region where the crop exists within the target region, and a vegetation index calculation unit (12) that calculates the vegetation index of the crop that exists in the region specified by the specification unit (11).
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公开(公告)号：US11255836B2
公开(公告)日：2022-02-22
申请号：US16338372
申请日：2017-03-22
Applicant: NEC CORPORATION
Inventor： Kosuke Ishida , Shinji Oominato , Masami Sakaguchi , Shunsuke Akimoto
Abstract: Provided are a soil estimation device, a soil estimation method and a program that are capable of improving the accuracy of estimation of a state in soil without increasing the number of sensors that detect the state in the soil. The soil estimation device 100 is provided with an estimated model generation unit 10. The estimated model generation unit 10 generates an estimated model based on at least one among geographical information that specifies a geographical feature of a field of interest and soil distribution information that specifies a soil distribution in the field. The estimated model is a model for estimating, from a measured value that indicates the state in the soil at one location within the field, the state in the soil at a location other than the one location.
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公开(公告)号：US11163996B2
公开(公告)日：2021-11-02
申请号：US16494117
申请日：2018-02-16
Applicant: NEC Corporation
Inventor： Kousuke Ishida , Hajime Ishikawa , Shinji Oominato , Shunsuke Akimoto , Masami Sakaguchi , Shintaro Matsumoto
Abstract: A vegetation index calculation apparatus (10) is provided with a learning model generation unit (11) that generates a learning model, by using an image of a crop targeted for calculation of a vegetation index and an image of plants other than the crop to learn a feature amount of the image of the crop, an image acquisition unit (12) that acquires an aerial image of a target region where the crop is being grown, a specification unit (13) that applies the aerial image acquired by the image acquisition unit (12) to the learning model generated by the learning model generation unit (11), and specifies the image of the crop in the aerial image acquired by the image acquisition unit (12), and a vegetation index calculation unit (14) that calculates the vegetation index of the crop, using the image of the crop specified by the specification unit (13).
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