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公开(公告)号：US20190287023A1
公开(公告)日：2019-09-19
申请号：US16294963
申请日：2019-03-07
申请人： Ryosuke Kasahara , Takuya Tanaka
发明人： Ryosuke Kasahara , Takuya Tanaka
摘要： A learning classification device includes a data memory, a learning unit, and a classification unit. The data memory is configured to store training data for learning a decision tree. The learning unit is configured to read a plurality of feature quantities included in the training data from the data memory by single access and derive data of a node based on the plurality of feature quantities, to learn the decision tree. The classification unit is configured to determine where the training data read from the data memory is to be split to from the node, based on the data of the node derived by the learning unit.
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公开(公告)号：US20210012240A1
公开(公告)日：2021-01-14
申请号：US16902611
申请日：2020-06-16
申请人： Takuya Tanaka , Ryosuke Kasahara , Akira Kinoshita
发明人： Takuya Tanaka , Ryosuke Kasahara , Akira Kinoshita
IPC分类号： G06N20/00
摘要： A learning device includes a learning unit configured to learn a model using learning data stored in a data storage unit; a subsampling unit configured to determine whether to use the learning data corresponding to gradient information updated by an update unit based on the model, for learning of a next model after learning of one model based on a subsampling rate; first and second buffer unit configured to buffer learning data determined to be used for and data determined not to be used for learning of the next model and gradient information corresponding to the learning data, respectively, up to a volume determined in advance. The first buffer unit and the second buffer unit are configured to write the learning data and the gradient information into the data storage unit for each predetermined block when buffering the learning data and the gradient information up to the volume.
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公开(公告)号：US10685432B2
公开(公告)日：2020-06-16
申请号：US15872257
申请日：2018-01-16
申请人： Ryosuke Kasahara , Takuya Tanaka
发明人： Ryosuke Kasahara , Takuya Tanaka
摘要： An apparatus and a method are disclosed, each of which applies a plurality of different spatial filters to one input image to generate a plurality of filtered images; calculates, for each of a plurality of pixels included in each of the plurality of filtered image, a score indicating a value determined by a difference from a corresponding one of a plurality of model groups, using the plurality of model groups that respectively correspond to the plurality of filtered images and each including one or more models having a parameter representing a target shape; calculates an integrated score indicating a result of integrating the scores of the respective plurality of pixels corresponding to each other over the plurality of filtered images; and determines an abnormality based on the integrated score.
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公开(公告)号：US20200050970A1
公开(公告)日：2020-02-13
申请号：US16527755
申请日：2019-07-31
申请人： Takuya Tanaka , Ryosuke Kasahara
发明人： Takuya Tanaka , Ryosuke Kasahara
摘要： A learning device is configured to perform learning of a decision tree. The learning device includes a gradient output unit and a branch score calculator. The gradient output unit is configured to output a cumulative sum of gradient information corresponding to each value of a feature amount of learning data. The branch score calculator is configured to calculate a branch score used for determining a branch condition for a node of the decision tree, from the cumulative sum without using a dividing circuit.
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公开(公告)号：US10043090B2
公开(公告)日：2018-08-07
申请号：US15365244
申请日：2016-11-30
申请人： Takuya Tanaka , Ryosuke Kasahara
发明人： Takuya Tanaka , Ryosuke Kasahara
摘要： An information processing device inspects a target image that contains an image of an inspection target. The information processing device includes a pre-processor, a first calculator, a second calculator, and a determiner. The pre-processor is configured to perform pre-processing for comparing the target image with a reference image or a plurality of reference images. The first calculator is configured to define, in the target image, a region of interest (ROI) and surrounding regions that are adjacent to the ROI, and calculate a feature value of the ROI. The second calculator is configured to calculate an outlier from comparison with feature values of images corresponding to the ROI and the surrounding regions in the reference images. The outlier numerically indicates singularity of an image at the ROI. The determiner is configured to provide, based on the outlier, an indicator to be used for the inspection.
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公开(公告)号：US10572993B2
公开(公告)日：2020-02-25
申请号：US15873070
申请日：2018-01-17
申请人： Takuya Tanaka , Ryosuke Kasahara
发明人： Takuya Tanaka , Ryosuke Kasahara
摘要： An information processing apparatus and method are disclosed, each of which: using a set of normal data, learns a first model for determining the normal data; sets, out of a plurality of abnormality candidate areas, the abnormality candidate areas selected by a user as correct data and the abnormality candidate areas not selected by the user as incorrect data, to learn a second model for identifying the correct data and the incorrect data, each abnormality candidate area indicating a candidate area of an abnormality and detected based on the first model from each of a plurality of captured images; obtains the captured images; detects the abnormality candidate areas from the respective captured images, using the first model; determines whether the abnormality candidate areas detected belong to the correct data or the incorrect data, using the second model; and controls to output a determination.
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公开(公告)号：US20200050933A1
公开(公告)日：2020-02-13
申请号：US16529121
申请日：2019-08-01
申请人： Takuya Tanaka , Ryosuke Kasahara
发明人： Takuya Tanaka , Ryosuke Kasahara
摘要： A learning device is configured to perform learning of a decision tree, and includes: a plurality of learning units each corresponding to a data memory of a plurality of data memories, and being configured to perform learning at a first node using learning data acquired by using first addresses related to a storage destination of the learning data corresponding to the first node of the decision tree in the data memory, and output a second address related to a storage destination of each piece of the learning data branched from the first node; and a plurality of managers each corresponding to a learning unit of the plurality of learning units, and being configured to calculate third addresses related to storage destinations of learning data corresponding to second nodes being next nodes of the first node using the first addresses and the second address output from the learning unit.
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公开(公告)号：US09706177B2
公开(公告)日：2017-07-11
申请号：US14359750
申请日：2012-11-27
申请人： Ryosuke Kasahara
发明人： Ryosuke Kasahara
CPC分类号： H04N7/183 , B60S1/0844 , G06K9/00791 , H04N5/2171 , H04N5/232 , H04N5/238
摘要： According to an embodiment, provided is an image processing system that includes: a light source that emits light; an imaging unit including an imaging element that captures light emitted and reflected from a foreign matter attached to the other surface of the transparent member and that captures light transmitted through the transparent member from the other surface side; and an image analyzing unit that analyzes captured image data. The captured image data is formed of a first image area frame used for detecting a foreign matter, and is formed of a second image area frame that corresponds to an effective imaging area excluding a predetermined area. Different rules are applied to read pixel data of between the first image area frame and the second image area frame.
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公开(公告)号：US09674459B2
公开(公告)日：2017-06-06
申请号：US14891229
申请日：2014-05-08
IPC分类号： H04N5/222 , H04N5/235 , G03B15/00 , H04N5/225 , G06T5/00 , G06K9/00 , G06K9/20 , G06T5/50 , G03B7/00
CPC分类号： H04N5/2355 , G03B15/00 , G06K9/00798 , G06K9/209 , G06T5/008 , G06T5/50 , G06T2207/20221 , G06T2207/30252 , G06T2207/30256 , H04N5/225 , H04N5/2351
摘要： An image processing system includes a brightness polarization superimposing unit. The brightness polarization superimposing unit superimposes, on a brightness image, polarization information of an image IMP that includes the polarization information, as a change in brightness of each pixel. The image processing system has a function of outputting an image obtained by superimposition by the brightness polarization superimposing unit as an output image IMO.
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10.发明申请公开(公告)号：US20150092080A1
公开(公告)日：2015-04-02
申请号：US14492479
申请日：2014-09-22
申请人： Go MARUYAMA , Ryosuke Kasahara , Taro Sawaki
发明人： Go MARUYAMA , Ryosuke Kasahara , Taro Sawaki
IPC分类号： H04N9/73
CPC分类号： H04N9/735 , H04N5/23206 , H04N5/3572 , H04N9/045
摘要： An image processing apparatus comprises: a white-balance processing unit that multiplies a first pixel that includes a plurality of colors constituting a pickup image that is picked up by an imaging unit by a gain value according to the colors and thereby generates a second pixel; a value adjusting unit that generates a third pixel by maintaining the second pixel that is equal to or smaller than a predetermined value out of the second pixel as it is, and by replacing, with the predetermined value, the second value that is larger than the predetermined value out of the second pixel; and a restoration processing unit that restores, by a restoration filter, resolution that has been reduced due to an optical system, on the third pixel.
摘要翻译： 一种图像处理装置，包括：白平衡处理单元，其将包括构成由成像单元拾取的拾取图像的多个颜色的第一像素乘以根据颜色的增益值，从而生成第二像素; 值调整单元，其通过将第二像素维持在第二像素以下的规定值以下的第二像素来生成第三像素，通过以规定值代替比第二像素大的第二值 第二像素之外的预定值; 以及恢复处理单元，其通过恢复滤波器在第三像素上恢复由于光学系统而被减小的分辨率。
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