专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明授权

US07783585B2 Data processing device, data processing method, and program 有权
标题翻译：数据处理装置，数据处理方法和程序
公开(公告)号：US07783585B2
公开(公告)日：2010-08-24
申请号：US11697238
申请日：2007-04-05
申请人： Kohtaro Sabe , Kazumi Aoyama , Jun Yokono , Kenichi Hidai , Kuniaki Noda
发明人： Kohtaro Sabe , Kazumi Aoyama , Jun Yokono , Kenichi Hidai , Kuniaki Noda
IPC分类号： G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00
CPC分类号： G06F15/18 , G06N3/0454 , G06N3/088
摘要： A data processing device for processing time-sequence data includes a learning unit for performing self-organizing learning of a SOM (self-organization map) making up a hierarchical SOM in which a plurality of SOMs are connected so as to construct a hierarchical structure, using, as SOM input data which is input to the SOM, a time-sequence of node information representing a winning node of a lower-order SOM which is at a lower hierarchical level from the SOM.
摘要翻译：一种用于处理时间序列数据的数据处理装置，包括：学习单元，用于执行构成其中连接有多个SOM的层次化SOM的SOM（自组织图）的自组织学习，以构建层次结构，使用作为输入到SOM的SOM输入数据，表示代表来自SOM的较低层级的低阶SOM的获胜节点的节点信息的时间序列。

2. 发明申请

US20070250461A1 Data Processing Device, Data Processing Method, and Program 有权
标题翻译：数据处理设备，数据处理方法和程序
公开(公告)号：US20070250461A1
公开(公告)日：2007-10-25
申请号：US11697238
申请日：2007-04-05
申请人： Kohtaro Sabe , Kazumi Aoyama , Jun Yokono , Kenichi Hidai , Kuniaki Noda
发明人： Kohtaro Sabe , Kazumi Aoyama , Jun Yokono , Kenichi Hidai , Kuniaki Noda
IPC分类号： G06F15/18
CPC分类号： G06F15/18 , G06N3/0454 , G06N3/088
摘要： A data processing device for processing time-sequence data includes a learning unit for performing self-organizing learning of a SOM (self-organization map) making up a hierarchical SOM in which a plurality of SOMs are connected so as to construct a hierarchical structure, using, as SOM input data which is input to the SOM, a time-sequence of node information representing a winning node of a lower-order SOM which is at a lower hierarchical level from the SOM.
摘要翻译：一种用于处理时间序列数据的数据处理装置，包括：学习单元，用于执行构成其中连接有多个SOM的层次化SOM的SOM（自组织图）的自组织学习，以构建层次结构，使用作为输入到SOM的SOM输入数据，表示代表来自SOM的较低层级的低阶SOM的获胜节点的节点信息的时间序列。

3. 发明授权

US08527434B2 Information processing device, information processing method, and program 有权
标题翻译：信息处理装置，信息处理方法和程序
公开(公告)号：US08527434B2
公开(公告)日：2013-09-03
申请号：US12791275
申请日：2010-06-01
申请人： Kuniaki Noda , Kohtaro Sabe , Yukiko Yoshiike , Kenta Kawamoto , Kenichi Hidai
发明人： Kuniaki Noda , Kohtaro Sabe , Yukiko Yoshiike , Kenta Kawamoto , Kenichi Hidai
IPC分类号： G06N5/00
CPC分类号： G06N3/006 , G06K9/00335 , G06K9/00664 , G06K9/6297
摘要： An information processing device includes: a learning section configured to learn a state transition probability model defined by state transition probability for each action of a state making a state transition due to an action performed by an agent capable of performing action and observation probability of a predetermined observed value being observed from the state, using an action performed by the agent and an observed value observed in the agent when the agent has performed the action.
摘要翻译：一种信息处理装置，包括：学习部，其被配置为：由于能够执行动作的代理和所述预定的行为的观察概率而进行的状态转换的状态的每个动作，学习由状态转移概率定义的状态转移概率模型观察到的值是从状态观察到的，使用由试剂进行的作用和在试剂进行作用时在试剂中观察到的观察值。

4. 发明申请

US20100318479A1 INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM 有权
标题翻译：信息处理设备，信息处理方法和程序
公开(公告)号：US20100318479A1
公开(公告)日：2010-12-16
申请号：US12791275
申请日：2010-06-01
申请人： Kuniaki NODA , Kohtaro Sabe , Yukiko Yoshiike , Kenta Kawamoto , Kenichi Hidai
发明人： Kuniaki NODA , Kohtaro Sabe , Yukiko Yoshiike , Kenta Kawamoto , Kenichi Hidai
IPC分类号： G06F15/18 , G06N5/02
CPC分类号： G06N3/006 , G06K9/00335 , G06K9/00664 , G06K9/6297
摘要： An information processing device includes: a learning section configured to learn a state transition probability model defined by state transition probability for each action of a state making a state transition due to an action performed by an agent capable of performing action and observation probability of a predetermined observed value being observed from the state, using an action performed by the agent and an observed value observed in the agent when the agent has performed the action.
摘要翻译：一种信息处理装置，包括：学习部，其被配置为：由于能够执行动作的代理以及预定的行为的观察概率，进行状态转换的状态的状态转移概率而定义的状态转移概率模型观察到的值是从状态观察到的，使用由试剂进行的作用和在试剂进行作用时在试剂中观察到的观察值。

5. 发明授权

US08560467B2 Apparatus, method, and program for predicting user activity state through data processing 有权
标题翻译：用于通过数据处理预测用户活动状态的装置，方法和程序
公开(公告)号：US08560467B2
公开(公告)日：2013-10-15
申请号：US12839321
申请日：2010-07-19
申请人： Masato Ito , Kohtaro Sabe , Hirotaka Suzuki , Jun Yokono , Kazumi Aoyama , Takashi Hasuo
发明人： Masato Ito , Kohtaro Sabe , Hirotaka Suzuki , Jun Yokono , Kazumi Aoyama , Takashi Hasuo
IPC分类号： G06F15/18
CPC分类号： G06K9/00335 , G06K9/00664 , G06K9/00778
摘要： A data processing apparatus includes an obtaining unit for obtaining time-series data, an activity model learning unit for learning an activity model representing a user activity state as a stochastic state transition model from the obtained time-series data, a recognition unit for recognizing a current user activity state by using the learned activity model, and a prediction unit for predicting a user activity state after a predetermined time elapses from a current time from the recognized current user activity state, wherein the prediction unit predicts the user activity state as an occurrence probability, and calculates the occurrence probabilities of the respective states on the basis of the state transition probability of the stochastic state transition model to predict the user activity state, while it is presumed that observation probabilities of the respective states at the respective times of the stochastic state transition model are an equal probability.
摘要翻译：数据处理装置包括：获取单元，用于获取时间序列数据;活动模型学习单元，用于从所获得的时间序列数据中学习表示用户活动状态的活动模型作为随机状态转换模型;识别单元，用于识别通过使用所学习的活动模型的当前用户活动状态，以及预测单元，用于在从所识别的当前用户活动状态起从当前时间经过预定时间之后预测用户活动状态，其中，所述预测单元将所述用户活动状态预测为发生概率，并且基于随机状态转换模型的状态转移概率来计算各个状态的发生概率以预测用户活动状态，同时假设在随机的各个时间的各个状态的观察概率状态转换模型是相等的概率。

6. 发明申请

US20110029465A1 DATA PROCESSING APPARATUS, DATA PROCESSING METHOD, AND PROGRAM 有权
标题翻译：数据处理设备，数据处理方法和程序
公开(公告)号：US20110029465A1
公开(公告)日：2011-02-03
申请号：US12839321
申请日：2010-07-19
申请人： Masato ITO , Kohtaro Sabe , Hirotaka Suzuki , Jun Yokono , Kazumi Aoyama , Takashi Hasuo
发明人： Masato ITO , Kohtaro Sabe , Hirotaka Suzuki , Jun Yokono , Kazumi Aoyama , Takashi Hasuo
IPC分类号： G06F15/18
CPC分类号： G06K9/00335 , G06K9/00664 , G06K9/00778
摘要： A data processing apparatus includes an obtaining unit configured to obtain time-series data from a wearable sensor, an activity model learning unit configured to learn an activity model representing a user activity state as a stochastic state transition model from the obtained time-series data, a recognition unit configured to recognize a current user activity state by using the activity model of the user obtained by the activity model learning unit, and a prediction unit configured to predict a user activity state after a predetermined time elapses from a current time from the current user activity state recognized by the recognition unit.
摘要翻译：数据处理装置包括获取单元，被配置为从可穿戴传感器获取时间序列数据;活动模型学习单元，被配置为从所获得的时间序列数据中学习表示用户活动状态的活动模型作为随机状态转换模型，识别单元，被配置为通过使用由活动模型学习单元获得的用户的活动模型来识别当前用户活动状态;以及预测单元，被配置为在从当前的当前时间经过预定时间之后预测用户活动状态用户活动状态由识别单元识别。

7. 发明授权

US08571315B2 Information processing apparatus, information processing method, and program 有权
标题翻译：信息处理装置，信息处理方法和程序
公开(公告)号：US08571315B2
公开(公告)日：2013-10-29
申请号：US13288231
申请日：2011-11-03
申请人： Kohtaro Sabe , Kenichi Hidai , Kiyoto Ichikawa
发明人： Kohtaro Sabe , Kenichi Hidai , Kiyoto Ichikawa
IPC分类号： G06K9/00 , G06K9/38 , G06K9/62 , G06K9/68
CPC分类号： G06K9/4614 , G06K9/6256
摘要： An information processing apparatus includes: a distinguishing unit which, by using an ensemble classifier, which includes a plurality of weak classifiers outputting weak hypotheses which indicates whether a predetermined subject is shown in an image in response to inputs of a plurality of features extracted from the image, and a plurality of features extracted from an input image, sequentially integrates the weak hypotheses output by the weak classifiers in regard to the plurality of features and distinguishes whether the predetermined subject is shown in the input image based on the integrated value. The weak classifier classifies each of the plurality of features to one of three or more sub-divisions based on threshold values, calculates sum divisions of the sub-divisions of the plurality of features as whole divisions into which the plurality of features is classified, and outputs, as the weak hypothesis, a reliability degree of the whole divisions.
摘要翻译：一种信息处理装置，包括：识别单元，其使用整体分类器，其包括输出弱假设的多个弱分类器，所述弱分类器指示响应于从所述图像提取的多个特征的输入，是否在图像中示出预定对象图像和从输入图像提取的多个特征，顺序地对由弱分类器输出的关于多个特征的弱假设进行积分，并且基于积分值区分输入图像中是否显示预定对象。所述弱分类器基于阈值将所述多个特征中的每一个分类为三个或更多个子分割中的一个，并且将所述多个特征的子分割的和除作为将所述多个特征分类成的整个分割，以及作为弱假设的输出是整个分区的可靠性程度。

8. 再颁专利

USRE43873E1 Device and method for detecting object and device and method for group learning 有权
标题翻译：用于组学习的物体和装置的检测装置及方法
公开(公告)号：USRE43873E1
公开(公告)日：2012-12-25
申请号：US13208123
申请日：2011-08-11
申请人： Kenichi Hidai , Kohtaro Sabe , Kenta Kawamoto
发明人： Kenichi Hidai , Kohtaro Sabe , Kenta Kawamoto
IPC分类号： G06K9/62 , G06K9/00
CPC分类号： G06K9/6282 , G06K9/00248 , G06K9/6256
摘要： An object detecting device for detecting an object in a given gradation image. A scaling section generates scaled images by scaling down a gradation image input from an image output section. A scanning section sequentially manipulates the scaled images and cutting out window images from them and a discriminator judges if each window image is an object or not. The discriminator includes a plurality of weak discriminators that are learned in a group by boosting and an adder for making a weighted majority decision from the outputs of the weak discriminators. Each of the weak discriminators outputs an estimate of the likelihood of a window image to be an object or not by using the difference of the luminance values between two pixels. The discriminator suspends the operation of computing estimates for a window image that is judged to be a non-object, using a threshold value that is learned in advance.
摘要翻译：一种用于检测给定灰度图像中的物体的物体检测装置。缩放部分通过缩小从图像输出部分输入的灰度图像来生成缩放图像。扫描部分顺序地操纵缩放图像并从中切出窗口图像，并且鉴别器判断每个窗口图像是否是对象。鉴别器包括通过升压在一组中学习的多个弱识别器和用于从弱识别器的输出进行加权多数决定的加法器。每个弱识别器通过使用两个像素之间的亮度值的差异来输出窗口图像成为对象的可能性的估计。鉴别器使用预先学习的阈值暂停对被判断为非对象的窗口图像的计算估计的操作。

9. 发明授权

US08290885B2 Information processing apparatus, information processing method, and computer program 有权
标题翻译：信息处理装置，信息处理方法和计算机程序
公开(公告)号：US08290885B2
公开(公告)日：2012-10-16
申请号：US12381499
申请日：2009-03-12
申请人： Kohtaro Sabe , Katsuki Minamino , Kenta Kawamoto , Hirotaka Suzuki , Kenichi Hidai
发明人： Kohtaro Sabe , Katsuki Minamino , Kenta Kawamoto , Hirotaka Suzuki , Kenichi Hidai
IPC分类号： G06F17/00 , G06N5/00
CPC分类号： G05B19/045 , G05B13/0265 , G05B2219/23288 , G06N99/005
摘要： An information processing apparatus includes: model learning means for self-organizing, on the basis of a state transition model having a state and state transition to be learned by using time series data as data in time series, an internal state from an observation signal obtained by a sensor; and controller learning means for performing learning for allocating a controller, which outputs an action, to each of transitions of a state or each of transition destination states in the state transition model indicating the internal state self-organized by the model learning means.
摘要翻译：信息处理装置包括：用于自组织的模型学习装置，基于具有通过使用时间序列数据作为时间序列数据而被学习的状态和状态转变的状态转换模型，从获得的观察信号获得的内部状态通过传感器; 以及控制器学习装置，用于在指示由模型学习装置自组织的内部状态的状态转换模型中执行学习以分配向控制器输出动作的状态或转换目的地状态中的每一个的转换。

10. 发明授权

US07657085B2 Information processing apparatus and method, recording medium, and program 有权
标题翻译：信息处理装置和方法，记录介质和程序
公开(公告)号：US07657085B2
公开(公告)日：2010-02-02
申请号：US11089229
申请日：2005-03-24
申请人： Kohtaro Sabe , Kenichi Hidai
发明人： Kohtaro Sabe , Kenichi Hidai
IPC分类号： G06K9/62 , G05B13/02
CPC分类号： G06K9/00248 , G06K9/6217 , G06K9/6256 , G06K9/6282
摘要： In an information processing apparatus, such as an image processing apparatus, positive samples and negative samples are learned by a number of weak classifiers. During learning by the weak classifiers, a value of weighted majority is calculated as a sum of products of the results of classification by the respective weak classifiers and associated weights, and a learning threshold is also calculated. When the number of negative samples is greater than or equal to one half of the number of positive samples, negative samples for which the value of weighted majority is less than the learning threshold are removed.
摘要翻译：在诸如图像处理装置的信息处理装置中，由许多弱分类器学习正样本和负样本。在弱分类器的学习期间，加权多数的值被计算为相应弱分类器和关联权重的分类结果的乘积之和，并且还计算学习阈值。当阴性样本的数量大于或等于阳性样本数量的一半时，取消加权多数值小于学习阈值的负样本。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式