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131. 发明申请

US20120263376A1 SUPERVISED AND SEMI-SUPERVISED ONLINE BOOSTING ALGORITHM IN MACHINE LEARNING FRAMEWORK 有权
标题翻译：监督和半监督的机器学习框架中的在线升压算法
公开(公告)号：US20120263376A1
公开(公告)日：2012-10-18
申请号：US13085329
申请日：2011-04-12
申请人： Fan Wang , Xinyu Xu , Chang Yuan , Petrus J.L. van Beek
发明人： Fan Wang , Xinyu Xu , Chang Yuan , Petrus J.L. van Beek
IPC分类号： G06K9/62
CPC分类号： G06K9/6256 , G06K9/6262
摘要： A method for classification of samples comprising providing a trained statistical model based upon a set of initial samples. Receiving a set of first samples and training a first statistical model base upon the first set of samples, where the first statistical model is of the same class as the trained statistical model. Receiving a set of second samples and training a second statistical model base upon the second set of samples, where the second statistical model is of the same class as the trained statistical model. The trained statistical model, the first statistical model, and the second statistical model, being independent of each other and collectively used to classify another sample.
摘要翻译：一种用于样本分类的方法，包括基于一组初始样本提供经过训练的统计模型。接收一组第一个样本，并基于第一组样本训练第一个统计模型，其中第一个统计模型与训练的统计模型具有相同的类别。接收一组第二样本并训练基于第二组样本的第二统计模型，其中第二统计模型与训练的统计模型具有相同的类别。经过训练的统计模型，第一个统计模型和第二个统计模型，彼此独立，并集体用于对另一个样本进行分类。

132. 发明申请

US20120203720A1 ROBUST PATTERN RECOGNITION SYSTEM AND METHOD USING SOCRATIC AGENTS 有权
公开(公告)号：US20120203720A1
公开(公告)日：2012-08-09
申请号：US13446942
申请日：2012-04-13
申请人： James K. Baker
发明人： James K. Baker
IPC分类号： G06F15/18
CPC分类号： G06K9/6256 , G06K9/6262
摘要： A computer-implemented pattern recognition method, system and program product, the method comprising in one embodiment: creating electronically a linkage between a plurality of models within a classifier module within a pattern recognition system such that any one of said plurality of models may be selected as an active model in a recognition process; creating electronically a null hypothesis between at least one model of said plurality of linked models and at least a second model among said plurality of linked models; accumulating electronically evidence to accept or reject said null hypothesis until sufficient evidence is accumulated to reject said null hypothesis in favor of one of said plurality of linked models or until a stopping criterion is met; and transmitting at least a portion of the electronically accumulated evidence or a summary thereof to accept or reject said null hypothesis to a pattern classifier module.

133. 发明授权

US08238604B2 System and method for validation of face detection in electronic images 失效
标题翻译：电子图像中面部检测验证的系统和方法
公开(公告)号：US08238604B2
公开(公告)日：2012-08-07
申请号：US12193390
申请日：2008-08-18
申请人： Jonathan Yen , Tony Quach
发明人： Jonathan Yen , Tony Quach
IPC分类号： G06K9/00
CPC分类号： G06K9/00228 , G06K9/6262
摘要： The subject application is directed to a system and method for validation of face detection in electronic images. Image data is first received along with at least one image portion that includes a possible facial depiction. Eye position data, nose position data, and mouth position data are also received. A reference point at a central location of the at least one image portion is then isolated. A width of the image portion is then isolated, and a facial region is isolated in accordance with the eye, nose, and mouth position data. The eye distance is then determined from the received eye position data. The isolated facial region data is then tested against the reference point and eye distance is tested against a width of the image portion. An output is generated corresponding to the accuracy of isolated facial region in accordance with the tests.
摘要翻译：本申请涉及用于验证电子图像中的人脸检测的系统和方法。首先接收图像数据以及包括可能的面部描绘的至少一个图像部分。眼睛位置数据，鼻位置数据和嘴位置数据也被接收。然后隔离至少一个图像部分的中心位置处的参考点。然后隔离图像部分的宽度，并且根据眼睛，鼻子和嘴部位置数据隔离面部区域。然后从接收到的眼睛位置数据确定眼睛距离。然后针对参考点测试孤立的面部区域数据，并针对图像部分的宽度测试眼睛距离。根据测试产生对应于孤立面部区域的准确度的输出。

135. 发明授权

US08086294B2 Unified probabilistic framework for predicting and detecting seizure onsets in the brain and multitherapeutic device 有权
标题翻译：用于预测和检测大脑和多治疗装置中的癫痫发作的统一概率框架
公开(公告)号：US08086294B2
公开(公告)日：2011-12-27
申请号：US11837814
申请日：2007-08-13
申请人： Javier Ramón Echauz , Brian Litt , Rosana Esteller , George John Vachtsevanos
发明人： Javier Ramón Echauz , Brian Litt , Rosana Esteller , George John Vachtsevanos
IPC分类号： A61B5/04 , G01N33/48 , G01N31/00
CPC分类号： A61B5/7267 , A61B5/0476 , A61B5/076 , A61B5/4094 , A61B5/7275 , A61N1/08 , A61N1/36017 , A61N1/36064 , A61N1/36082 , A61N1/36135 , G06F19/00 , G06F19/3456 , G06F19/3481 , G06K9/6262 , G06K9/627 , G06K9/6278 , G16H50/20 , G16H50/50
摘要： A method and system for assessing a quality of life index to adjust an implanted device to optimize patient-specific feature signals and treatment therapies. Accumulated energy of intracranial electroencephalogram (IEEG) signals is calculated over multiple data channels during seizures over a fixed time period. Accumulated energy of a treatment control is calculated over the multiple data channels over all times of activation of the implanted device over the fixed time period. The accumulated energy of both the IEEG signals and treatment control are weighted by seizure and treatment factors to determine a quality value for the fixed time period. A quality of life index is determined as a weighted average of current and previous quality values for a plurality of fixed time periods.
摘要翻译：一种用于评估生活质量指数以调整植入装置以优化患者特异性特征信号和治疗疗法的方法和系统。在固定时间段内癫痫发作期间，通过多个数据通道计算颅内脑电图（IEEG）信号的累积能量。在固定时间段内在植入装置的所有激活时间内，通过多个数据通道计算处理控制的累积能量。 IEEG信号和治疗控制的累积能量通过扣押和处理因子加权，以确定固定时间段的质量值。生活质量指数被确定为多个固定时间段的当前和先前质量值的加权平均值。

136. 发明申请

US20110280474A1 AUTO CLASSIFYING IMAGES AS "IMAGE NOT AVAILABLE" IMAGES 有权
标题翻译：自动分类图像为“图像不可用”图像
公开(公告)号：US20110280474A1
公开(公告)日：2011-11-17
申请号：US12777695
申请日：2010-05-11
申请人： Nabeel Kaushal , Feng Qi , Marcelo De Barros , Manish Mittal
发明人： Nabeel Kaushal , Feng Qi , Marcelo De Barros , Manish Mittal
IPC分类号： G06K9/62 , G06K9/00
CPC分类号： G06K9/6256 , G06K9/036 , G06K9/6262
摘要： An image may be accepted from a vendor, and the image may be submitted to an image analysis system. The image analysis system may determine whether the image is a not found image or a true image. The determination may occur in a variety of ways by examining the color and intensity characteristics of an image. After the analysis, a determination is received from the image analysis system of whether the image is a not found image or a true image.
摘要翻译：可以从供应商接受图像，并且图像可以被提交到图像分析系统。图像分析系统可以确定图像是未找到的图像还是真实图像。可以通过检查图像的颜色和强度特性以各种方式进行确定。在分析之后，从图像分析系统接收到图像是否是未找到的图像还是真实图像的确定。

138. 发明授权

US08041659B2 Systems and methods for motion recognition using multiple sensing streams 有权
标题翻译：使用多个感测流的运动识别的系统和方法
公开(公告)号：US08041659B2
公开(公告)日：2011-10-18
申请号：US12885301
申请日：2010-09-17
申请人： Xiaoyuan Tu , Yoichiro Kawano , Charles Musick, Jr. , William Robert Powers, III , Stuart Reynolds , Dana Wilkinson , Ian Wright , Wei Yen
发明人： Xiaoyuan Tu , Yoichiro Kawano , Charles Musick, Jr. , William Robert Powers, III , Stuart Reynolds , Dana Wilkinson , Ian Wright , Wei Yen
IPC分类号： G06F15/18
CPC分类号： G06F3/038 , A63F13/428 , G06F3/0346 , G06F2203/0384 , G06K9/6262 , G06K9/627
摘要： Techniques for motion recognition using multiple data streams are disclosed. Multiple data streams from inertia sensors as well as non-inertial sensors are received to derive a motion recognition signal from motion recognizers. These motion recognizers are originally constructed from a training set of motion signals and may be updated with received multiple sensing signals. In one aspect, multiple data streams are converted to device-independent motion signals that are applied with the motion recognizers to provide a generalized motion recognition capability.
摘要翻译：公开了使用多个数据流的运动识别技术。接收来自惯性传感器和非惯性传感器的多个数据流以从运动识别器导出运动识别信号。这些运动识别器最初由运动信号的训练集合构成，并且可以用接收到的多个感测信号进行更新。在一个方面，将多个数据流转换成与运动识别器一起应用的与设备无关的运动信号，以提供广义的运动识别能力。

139. 发明授权

US08027939B2 Automatic labeler assignment using a model built from multi-labeler data 有权
标题翻译：使用由多标签器数据构建的模型进行自动标签分配
公开(公告)号：US08027939B2
公开(公告)日：2011-09-27
申请号：US12893008
申请日：2010-09-29
申请人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
发明人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
IPC分类号： G06F15/18 , G06K9/00 , G06K9/62
CPC分类号： G06K9/6256 , G06F19/00 , G06K9/6226 , G06K9/6262 , G06N99/005 , G16H40/20
摘要： A method, including receiving multi-labeler data that includes data points labeled by a plurality of labelers; building a model from the multi-labeler data, wherein the model includes an input variable that corresponds to the data points, a label variable that corresponds to true labels for the data points, and variables for the labels given by the labelers; and executing the model, in response to receiving new data points, to determine a level of expertise of the labelers for the new data points.
摘要翻译：一种方法，包括接收包括由多个标签器标记的数据点的多标签器数据; 从所述多标签器数据构建模型，其中所述模型包括对应于所述数据点的输入变量，对应于所述数据点的真实标签的标签变量以及由所述标签器给出的标签的变量; 并且响应于接收到新的数据点执行该模型，以确定新数据点的标签器的专业水平。

140. 发明申请

US20110071967A1 Automatic Labeler Assignment 有权
标题翻译：自动贴标机分配
公开(公告)号：US20110071967A1
公开(公告)日：2011-03-24
申请号：US12893008
申请日：2010-09-29
申请人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
发明人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
IPC分类号： G06F15/18
CPC分类号： G06K9/6256 , G06F19/00 , G06K9/6226 , G06K9/6262 , G06N99/005 , G16H40/20
摘要： A method, including receiving multi-labeler data that includes data points labeled by a plurality of labelers; building a model from the multi-labeler data, wherein the model includes an input variable that corresponds to the data points, a label variable that corresponds to true labels for the data points, and variables for the labels given by the labelers; and executing the model, in response to receiving new data points, to determine a level of expertise of the labelers for the new data points.
摘要翻译：一种方法，包括接收包括由多个标签器标记的数据点的多标签器数据; 从所述多标签器数据构建模型，其中所述模型包括对应于所述数据点的输入变量，对应于所述数据点的真实标签的标签变量以及由所述标签器给出的标签的变量; 并且响应于接收到新的数据点执行该模型，以确定新数据点的标签器的专业水平。

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