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公开(公告)号：US09282296B2
公开(公告)日：2016-03-08
申请号：US13693231
申请日：2012-12-04
申请人： Xiang Gao , Vinay Damodar Shet , Xianjun S. Zheng , Sushil Mittal , Mayank Rana , Maneesh Kumar Singh , Bernhard Agthe , Andreas Hutter
发明人： Xiang Gao , Vinay Damodar Shet , Xianjun S. Zheng , Sushil Mittal , Mayank Rana , Maneesh Kumar Singh , Bernhard Agthe , Andreas Hutter
IPC分类号： H04N7/18 , H04N5/77 , G08B13/196
CPC分类号： H04N7/181 , G08B13/19645 , G08B13/1968
摘要： Multiple cameras are configured for use in video analytics. A single configuration tool is provided. The interrelationships between cameras are included within the configuration. Using a combination of text entry fields, registration of the cameras on a floor or other map, and marking on images from the cameras, an efficient workflow for configuration may be provided.
摘要翻译： 配置多个摄像机用于视频分析。 提供了一个单一的配置工具。 相机之间的相互关系包含在配置内。 使用文本输入字段的组合，将相机注册在地板或其他地图上，并且对来自相机的图像进行标记，可以提供有效的配置工作流程。
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公开(公告)号：US20130147961A1
公开(公告)日：2013-06-13
申请号：US13693231
申请日：2012-12-04
申请人： Xiang Gao , Vinay Damodar Shet , Xianjun S. Zheng , Sushil Mittal , Mayank Rana , Maneesh Kumar Singh , Bernhard Agthe , Andreas Hutter
发明人： Xiang Gao , Vinay Damodar Shet , Xianjun S. Zheng , Sushil Mittal , Mayank Rana , Maneesh Kumar Singh , Bernhard Agthe , Andreas Hutter
IPC分类号： H04N7/18
CPC分类号： H04N7/181 , G08B13/19645 , G08B13/1968
摘要： Multiple cameras are configured for use in video analytics. A single configuration tool is provided. The interrelationships between cameras are included within the configuration. Using a combination of text entry fields, registration of the cameras on a floor or other map, and marking on images from the cameras, an efficient workflow for configuration may be provided.
摘要翻译： 配置多个摄像机用于视频分析。 提供了一个单一的配置工具。 相机之间的相互关系包含在配置内。 使用文本输入字段的组合，将相机注册在地板或其他地图上，并且对来自相机的图像进行标记，可以提供有效的配置工作流程。
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3.发明申请公开(公告)号：US20120243741A1
公开(公告)日：2012-09-27
申请号：US13397924
申请日：2012-02-16
CPC分类号： G06K9/6296 , G06K2209/09
摘要： A method of detecting an object in image data that is deemed to be a threat includes annotating sections of at least one training image to indicate whether each section is a component of the object, encoding a pattern grammar describing the object using a plurality of first order logic based predicate rules, training distinct component detectors to each identify a corresponding one of the components based on the annotated training images, processing image data with the component detectors to identify at least one of the components, and executing the rules to detect the object based on the identified components.
摘要翻译： 一种检测被认为是威胁的图像数据中的对象的方法包括：注释至少一个训练图像的部分，以指示每个部分是否是对象的组件，使用多个第一顺序对描述对象的模式语法进行编码 基于逻辑的谓词规则，训练不同的分量检测器，以基于所标注的训练图像来识别相应的一个分量，使用分量检测器处理图像数据以识别组件中的至少一个，以及执行规则以检测基于对象 对所识别的组件。
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4.发明授权公开(公告)号：US08903128B2
公开(公告)日：2014-12-02
申请号：US13397924
申请日：2012-02-16
CPC分类号： G06K9/6296 , G06K2209/09
摘要： A method of detecting an object in image data that is deemed to be a threat includes annotating sections of at least one training image to indicate whether each section is a component of the object, encoding a pattern grammar describing the object using a plurality of first order logic based predicate rules, training distinct component detectors to each identify a corresponding one of the components based on the annotated training images, processing image data with the component detectors to identify at least one of the components, and executing the rules to detect the object based on the identified components.
摘要翻译： 一种检测被认为是威胁的图像数据中的对象的方法包括：注释至少一个训练图像的部分，以指示每个部分是否是对象的组件，使用多个第一顺序对描述对象的模式语法进行编码 基于逻辑的谓词规则，训练不同的分量检测器，以基于所标注的训练图像来识别相应的一个分量，使用分量检测器处理图像数据以识别组件中的至少一个，以及执行规则以检测基于对象 对所识别的组件。
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5.发明授权公开(公告)号：US08548231B2
公开(公告)日：2013-10-01
申请号：US12724954
申请日：2010-03-16
申请人： Vinay Damodar Shet , Maneesh Kumar Singh , Claus Bahlmann , Visvanathan Ramesh , Stephen P. Masticola , Jan Neumann , Toufiq Parag , Michael A. Gall , Roberto Antonio Suarez
发明人： Vinay Damodar Shet , Maneesh Kumar Singh , Claus Bahlmann , Visvanathan Ramesh , Stephen P. Masticola , Jan Neumann , Toufiq Parag , Michael A. Gall , Roberto Antonio Suarez
CPC分类号： G06K9/00369 , G06K9/626
摘要： First order predicate logics are provided, extended with a bilattice based uncertainty handling formalism, as a means of formally encoding pattern grammars, to parse a set of image features, and detect the presence of different patterns of interest implemented on a processor. Information from different sources and uncertainties from detections, are integrated within the bilattice framework. Automated logical rule weight learning in the computer vision domain applies a rule weight optimization method which casts the instantiated inference tree as a knowledge-based neural network, to converge upon a set of rule weights that give optimal performance within the bilattice framework. Applications are in (a) detecting the presence of humans under partial occlusions and (b) detecting large complex man made structures in satellite imagery (c) detection of spatio-temporal human and vehicular activities in video and (c) parsing of Graphical User Interfaces.
摘要翻译： 提供了第一级谓词逻辑，扩展了基于双精度的不确定性处理形式，作为正式编码模式语法的手段，解析一组图像特征，并检测在处理器上实现的不同兴趣模式的存在。 来自不同来源的信息和来自检测的不确定性，被集成在双层框架内。 计算机视觉领域中的自动逻辑规则权重学习应用规则权重优化方法，该方法将实例化推理树作为基于知识的神经网络进行聚合，以收敛于在边界框架内提供最佳性能的一组规则权重。 应用是（a）检测部分闭塞下人的存在，（b）检测卫星图像中的大型复杂人造结构（c）检测视频中的时空人类和车辆活动，（c）解析图形用户界面 。
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6.发明申请Predicate Logic based Image Grammars for Complex Visual Pattern Recognition 有权基于逻辑逻辑的图像语法用于复杂视觉模式识别公开(公告)号：US20100278420A1
公开(公告)日：2010-11-04
申请号：US12724954
申请日：2010-03-16
申请人： Vinay Damodar Shet , Maneesh Kumar Singh , Claus Bahlmann , Visvanathan Ramesh , Stephen P. Masticola , Jan Neumann , Toufiq Parag , Michael A. Gall , Roberto Antonio Suarez
发明人： Vinay Damodar Shet , Maneesh Kumar Singh , Claus Bahlmann , Visvanathan Ramesh , Stephen P. Masticola , Jan Neumann , Toufiq Parag , Michael A. Gall , Roberto Antonio Suarez
CPC分类号： G06K9/00369 , G06K9/626
摘要： First order predicate logics are provided, extended with a bilattice based uncertainty handling formalism, as a means of formally encoding pattern grmmars, to parse a set of image features, and detect the presence of different patterns of interest implemented on a processor. Information from different sources and uncertainties from detections, are integrated within the bilattice framework. Automated logical rule weight learning in the computer vision domain applies a rule weight optimization method which casts the instantiated inference tree as a knowledge-based neural network, to converge upon a set of rule weights that give optimal performance within the bilattice framework. Applications are in (a) detecting the presence of humans under partial occlusions and (b) detecting large complex man made structures in satellite imagery (c) detection of spatio-temporal human and vehicular activities in video and (c) parsing of Graphical User Interfaces.
摘要翻译： 提供了第一级谓词逻辑，扩展了基于二进制的不确定性处理形式，作为正式编码模式格式的手段，解析一组图像特征，以及检测在处理器上实现的不同感兴趣模式的存在。 来自不同来源的信息和来自检测的不确定性，被集成在双层框架内。 计算机视觉领域中的自动逻辑规则权重学习应用规则权重优化方法，该方法将实例化推理树作为基于知识的神经网络进行聚合，以收敛于在边界框架内提供最佳性能的一组规则权重。 应用是（a）检测部分闭塞下人的存在，（b）检测卫星图像中的大型复杂人造结构（c）检测视频中时空人类和车辆的活动，（c）解析图形用户界面 。
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公开(公告)号：US20160292372A1
公开(公告)日：2016-10-06
申请号：US14442517
申请日：2013-11-15
CPC分类号： G16H50/20 , G06N3/0472 , G06N3/08
摘要： A method of identifying an optimum treatment for a patient suffering from coronary artery disease, comprising: (i) providing patient information selected from: (a) status in the patient of one or more coronary disease associated biomarkers; (b) one or more items of medical history information selected from prior condition history, intervention history and medication history; (c) one or more items of diagnostic history, if the patient has a diagnostic history; and (d) one or more items of demographic data; (ii) aggregating the patient information in: (a) a Bayesian network; (b) a machine learning and neural network; (c) a rule-based system; and (d) a regression-based system; (iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome.
摘要翻译： 一种鉴定患有冠状动脉疾病的患者的最佳治疗的方法，包括：（i）提供患者信息，所述患者信息选自：（a）患者中一种或多种冠状动脉疾病相关生物标志物的状态; （b）从先前情况史，干预史和用药史选择的一项或多项病史信息; （c）患者具有诊断史的一项或多项诊断史; 和（d）一个或多个人口统计数据项目; （ii）在以下方面聚合患者信息：（a）贝叶斯网络; （b）机器学习和神经网络; （c）基于规则的制度; 和（d）基于回归的系统; （iii）通过放置裸金属支架或药物涂层的支架，导出包括经皮冠状动脉介入的每个干预的预测概率不良事件结果; 或通过冠状动脉旁路移植术; 和（iv）确定具有最低预测概率不良结果的干预。
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8.发明授权Method and system for cooperative diversity visual cognition in wireless video sensor networks 有权无线视频传感器网络中协同多样性视觉认知的方法与系统公开(公告)号：US09398268B2
公开(公告)日：2016-07-19
申请号：US13480064
申请日：2012-05-24
CPC分类号： H04N7/181
摘要： A method and system for cooperative diversity visual cognition in a wireless sensor network is disclosed. The method and system are capable of solving distributed visual cognition tasks (for example, online simultaneous reconstruction of 3D models of a large area) by using multiple video streams and exploiting cooperative diversity video sensing information while ensuring an optimal tradeoff between energy consumption and video quality of images received from said multiple video streams.
摘要翻译： 本发明公开了一种无线传感器网络中的协同分集视觉认知的方法和系统。 该方法和系统能够通过使用多个视频流解决分布式视觉认知任务（例如，大面积的3D模型的在线同时重建），并利用协同分集视频传感信息，同时确保能量消耗与视频质量之间的最佳权衡 从所述多个视频流接收的图像。
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9.发明申请公开(公告)号：US20190325861A1
公开(公告)日：2019-10-24
申请号：US16387644
申请日：2019-04-18
摘要： Systems and methods for automatic speech recognition by training a neural network to learn features from raw speech. The system comprises a neural network executing on a computer system and comprising a feature extractor, a label classifier, and a domain classifier. The feature extractor processes raw speech data and generates a first output data. The label classifier processes the first output data and generates a second output data. The domain classifier processes the first output data and generating a third output data. The neural network calculates first loss data based on the second output, and second loss data based on the third output. Further, the neural network is trained to minimize a cross-entropy cost of the label classifier and to maximize a cross-entropy cost of the domain classifier using the first loss data and the second loss data.
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10.发明申请Method and System for Cooperative Diversity Visual Cognition in Wireless Video Sensor Networks 有权无线视频传感器网络中协作多样性视觉认知的方法与系统公开(公告)号：US20120300068A1
公开(公告)日：2012-11-29
申请号：US13480064
申请日：2012-05-24
IPC分类号： H04N7/18
CPC分类号： H04N7/181
摘要： A method and system for cooperative diversity visual cognition in a wireless sensor network is disclosed. The method and system are capable of solving distributed visual cognition tasks (for example, online simultaneous reconstruction of 3D models of a large area) by using multiple video streams and exploiting cooperative diversity video sensing information while ensuring an optimal tradeoff between energy consumption and video quality of images received from said multiple video streams.
摘要翻译： 公开了一种在无线传感器网络中进行协同多样化视觉认知的方法和系统。 该方法和系统能够通过使用多个视频流解决分布式视觉认知任务（例如，大面积的3D模型的在线同时重建），并利用协同分集视频传感信息，同时确保能量消耗与视频质量之间的最佳权衡 从所述多个视频流接收的图像。
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