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公开(公告)号：US20240184103A1
公开(公告)日：2024-06-06
申请号：US18285967
申请日：2022-01-13
Applicant: HAMAMATSU PHOTONICS K.K.
Inventor： Masashi FUKUHARA , Yu HASHIMOTO , Kazuya SUZUKI , Tomoko HYODO
CPC classification number: G02B27/0012 , G02B27/0025 , G06N20/00
Abstract: A control device includes: an acquisition unit that acquires, for an intensity image obtained by observing an action caused by light corrected using a spatial light modulator based on a Zernike coefficient, an intensity distribution that is a distribution of intensities in a plurality of regions of interest within a predetermined range on the intensity image; a generation unit that calculates a comparison result between the intensity distribution and a target distribution to generate comparison data; and a prediction unit that predicts a Zernike coefficient, which is for performing aberration correction related to the light so that the intensity distribution approaches the target distribution, by inputting the comparison data and the Zernike coefficient, which is a basis of the intensity distribution, to a learning model.
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公开(公告)号：US20240185125A1
公开(公告)日：2024-06-06
申请号：US18285954
申请日：2022-01-13
Applicant: HAMAMATSU PHOTONICS K.K.
Inventor： Masashi FUKUHARA , Yu HASHIMOTO , Kazuya SUZUKI , Tomoko HYODO
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: A control device includes: an acquisition unit that acquires an intensity distribution along a predetermined direction for an intensity image obtained by observing an action caused by light corrected using a spatial light modulator based on a Zernike coefficient; a generation unit that calculates a comparison result between the intensity distribution and a target distribution to generate comparison data; and a prediction unit that predicts a Zernike coefficient, which is for performing aberration correction related to the light so that the intensity distribution approaches the target distribution, by inputting the comparison data and the Zernike coefficient, which is a basis of the intensity distribution, to a learning model.
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公开(公告)号：US20220172045A1
公开(公告)日：2022-06-02
申请号：US17437871
申请日：2020-02-25
Applicant: HAMAMATSU PHOTONICS K.K.
Inventor： Masashi FUKUHARA , Kazuhiko FUJIWARA , Yoshihiro MARUYAMA
Abstract: A convolutional neural network decision basis extraction apparatus includes a contribution rate calculation unit and a basis extraction unit. The contribution rate calculation unit obtains a contribution rate of a weight of a fully connected layer to an output label of an output layer. The basis extraction unit extracts a decision basis of a CNN based on a feature map input to the fully connected layer, the weight of the fully connected layer, and the above contribution rate.
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公开(公告)号：US20210190679A1
公开(公告)日：2021-06-24
申请号：US16755720
申请日：2018-09-26
Applicant: HAMAMATSU PHOTONICS K.K.
Inventor： Masashi FUKUHARA , Kazuhiko FUJIWARA , Yoshihiro MARUYAMA
Abstract: A spectrum analysis apparatus is an apparatus for analyzing an analysis object on the basis of a spectrum of light generated in the analysis object containing any one or two or more of a plurality of reference objects, and includes an array conversion unit, a processing unit, a learning unit, and an analysis unit. The array conversion unit generates two-dimensional array data on the basis of a spectrum of light generated in the reference object or the analysis object. The processing unit includes a deep neural network. The analysis unit causes the array conversion unit to generate the two-dimensional array data on the basis of the spectrum of light generated in the analysis object, inputs the two-dimensional array data to the deep neural network, and analyzes the analysis object on the basis of data output from the deep neural network.
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