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1. 发明公开

EP3311110A1 METHOD AND APPARATUS FOR REPRESENTING MAP ELEMENT AND METHOD AND APPARATUS FOR LOCATING VEHICLE/ROBOT 审中-实审
标题翻译：用于表示地图元素的方法和设备以及用于定位车辆/机器人的方法和设备
公开(公告)号：EP3311110A1
公开(公告)日：2018-04-25
申请号：EP15895243.2
申请日：2015-06-18
申请人： Bayerische Motoren Werke Aktiengesellschaft
发明人： ISERT, Carsten , JIANG, Wanli , LI, Qianshan
IPC分类号： G01C21/30
CPC分类号： G06K9/6251 , G01C21/3635 , G05D1/0231 , G06K9/00664 , G06T17/10
摘要： A method and an apparatus are provided for representing a map element and for locating a vehicle/robot based thereupon. The method for representing a map element includes: generating a Gaussian Mixture Model for the map element; generating a signature for identifying the map element, wherein the signature includes properties of the map element; and generating a Signatured Gaussian Mixture Model for representing the map element, wherein the Signatured Gaussian Mixture Model includes the Gaussian Mixture Model and the signature.

2. 发明公开

EP3063656A4 EFFICIENT DISTANCE METRIC LEARNING FOR FINE-GRAINED VISUAL CATEGORIZATION 审中-公开
标题翻译： EFFENIENTES LERNEN VON ABSTANDSMETRIKENFÜRFEINKÖRNIGEVISUELLE KATEGORISIERUNG
公开(公告)号：EP3063656A4
公开(公告)日：2017-07-05
申请号：EP14858662
申请日：2014-10-29
申请人： NEC LAB AMERICA INC
发明人： ZHU SHENGHUO , LIN YUANQING , QIAN QI
IPC分类号： G06F17/00
CPC分类号： G06K9/6201 , G06K9/6232 , G06K9/6251

3. 发明公开

EP2707836A4 SYSTEM AND METHOD FOR COMPACT DESCRIPTOR FOR VISUAL SEARCH 审中-公开
标题翻译：系统VERFAHRENFÜREINEN KOMPAKTEN DESKRIPTORSFÜRVISUELLE SUCHEN
公开(公告)号：EP2707836A4
公开(公告)日：2014-06-18
申请号：EP12797441
申请日：2012-01-04
申请人： HUAWEI TECH CO LTD
发明人： XIN XIN , LI ZHU , KATSAGGELOS AGGELOS K
IPC分类号： G06K9/46
CPC分类号： G06K7/1447 , G06K9/4671 , G06K9/6251 , G06K9/6276

4. 发明公开

EP2491518A2 METHODE ET SYSTÈME POUR ÉVALUER LA RESSEMBLANCE D'UN OBJET REQUÊTE À DES OBJETS DE RÉFÉRENCE 审中-公开
标题翻译：方法和系统相似度之间的查询对象和引用对象评估
公开(公告)号：EP2491518A2
公开(公告)日：2012-08-29
申请号：EP10768037.3
申请日：2010-10-22
申请人： Commissariat à l'Énergie Atomique et aux Énergies Alternatives
发明人： AUPETIT, Mickael , LESPINATS, Sylvain
IPC分类号： G06K9/62 , G06F7/02 , G06F17/15
CPC分类号： G06K9/6251 , G06F17/16 , G06F17/30011 , G06F17/301
摘要： The present invention relates to a method and system for evaluating the class of a test datum in a data space having a dimension D, where D ≥ 3, each datum belonging to at least one class grouping together a plurality of data. The method comprises a step of projecting a set of reference data of the data space into a space having a dimension Q, where Q

5. 发明公开

EP2477086A1 ANOMALY DETECTION AND DIAGNOSTIC METHOD, ANOMALY DETECTION AND DIAGNOSTIC SYSTEM, AND ANOMALY DETECTION AND DIAGNOSTIC PROGRAM 审中-公开
标题翻译： FOR条件检测和诊断，DEVICE METHODS FOR检测条件，诊断和PROGRAM FOR条件检测和诊断
公开(公告)号：EP2477086A1
公开(公告)日：2012-07-18
申请号：EP10813558.3
申请日：2010-06-16
申请人： Hitachi, Ltd.
发明人： MAEDA Shunji , SHIBUYA Hisae
IPC分类号： G05B23/02 , G06Q50/00
CPC分类号： G05B23/0227 , G06K9/00536 , G06K9/6251
摘要： Provided is an anomaly detection method and system capable of constructing determination condition rules of anomaly detection from case-based anomaly detection by way of multivariate analysis of a multi-dimensional sensor signal, applying the rules to design-based anomaly detection of individual sensor signals, and also appropriately executing setting and control of threshold values for highly sensitive, early, and clearly visible detection of anomalies. Anomaly detection on the basis of a case base by way of multivariate analysis controls design-based anomaly detection. That is to say, (1) anomaly detection on the basis of a case base performs selection of sensor signals and anomaly detection according to various types of anomalies. Specifically, anomaly detection (characteristic conversion), evaluation of level of effect of each signal, construction of determination conditions (rules), and display and selection of sensor signals corresponding to the anomaly are performed. (2) Design-based anomaly detection for individual sensor signals performs anomaly detection after the above have been performed. Specifically, setting and control of thresholds, display of thresholds, and anomaly detection and display are performed.
摘要翻译：本发明提供一种异常检测方法，并且能够通过一个多维传感器信号的多变量分析的方式，从基于案例的异常检测构建异常检测的判定条件的规则，将规则应用于的系统设计为基础的异常检测各个传感器信号的，等适当地执行阈值的设定和控制，高度敏感的，早期和清晰可见的异常的检测。通过多变量分析的方式的情况下，基体的基础上，异常检测控制设计为基础的异常检测。也就是说，（1）的情况下，基体的基础上，异常检测执行传感器信号和异常检测gemäß的选择各种类型的异常。具体地，异常检测（特性转换），每个信号的效果水平评价，进行的确定条件（规则），并显示和传感器信号对应于所述异常的选择结构。（2）基于设计的异常检测为单独的传感器信号进行上述已被执行之后的异常检测。具体而言，进行设定和阈值的控制，阈值的显示，以及异常检测和显示。

6. 发明公开

EP2401686A1 VIDEO SEGMENTATION 有权转让
标题翻译： VIDEOSEGMENTIERUNG
公开(公告)号：EP2401686A1
公开(公告)日：2012-01-04
申请号：EP10706317.4
申请日：2010-02-26
申请人： British Telecommunications Public Limited Company
发明人： XU, Li-Qun , ANJULAN, Arasanathan
IPC分类号： G06F17/30
CPC分类号： G06F17/30843 , G06K9/00765 , G06K9/6224 , G06K9/6251
摘要： A method of segmenting a sequence of video images according to scene activity, the method comprising: defining a first series of nodes in a first multi-dimensional space, each node corresponding to an image of the sequence of video images; defining a transformation function that maps each of the first series of nodes to a corresponding node in a second multi-dimensional space having a lower dimensionality than the first multi-dimensional space; applying said transformation function to each of the first series of nodes to define a second series of respective nodes in the second multi-dimensional space; applying a data clustering algorithm to the second series of nodes to identify clusters of nodes within the second multi-dimensional space, the data clustering algorithm being constrained by a measure of feature distance between a pair of clusters of nodes and a measure of temporal distance between the pair of clusters of nodes; determining a representative image from each cluster of nodes and plotting each representative image with respect to a measure of the elapsed time of the sequence of video images to form an scene density curve indicating the underlying scene change activities; and segmenting the sequence of video images in accordance with local minima and/or maxima of the scene density curve.
摘要翻译：一种根据场景活动分割视频图像序列的方法，所述方法包括：在第一多维空间中定义第一系列节点，每个节点对应于视频图像序列的图像; 定义将所述第一系列节点中的每一个映射到具有比所述第一多维空间小的维度的第二多维空间中的对应节点的变换函数; 将所述变换函数应用于所述第一系列节点中的每一个以限定所述第二多维空间中的相应节点的第二系列; 将数据聚类算法应用于第二系列节点以识别第二多维空间内的节点簇，所述数据聚类算法受到一对节点簇之间的特征距离的测量以及时间距离的度量一对节点簇; 确定来自每个节点簇的代表图像，并针对所述视频图像序列的经过时间的度量来绘制每个代表图像，以形成指示下一个场景变化活动的场景desnity曲线; 以及根据场景极化曲线的局部最小值和/或最大值来分割视频图像的序列。

7. 发明公开

EP2348457A1 Activity monitoring system 审中-公开
标题翻译： Aktivitätsüberwachungssystem
公开(公告)号：EP2348457A1
公开(公告)日：2011-07-27
申请号：EP10250095.6
申请日：2010-01-21
申请人： British Telecommunications public limited company
发明人： Tateson, Jane, Elizabeth
IPC分类号： G06K9/62
CPC分类号： G06K9/6251 , G06K9/6215 , G06K9/6284
摘要： A system for monitoring and classifying activities uses data derived from a sensor, which is perturbed by the performance of an activity, to generate a distribution of states within a self organising map (SOM). This distribution of states can be compared with a reference distribution of states, allowing the activity to be compared to the activity that was used in the generation of the reference distribution of states.
摘要翻译：用于监测和分类活动的系统使用由传感器导出的数据，该传感器受到活动的性能的干扰，以产生自组织映射（SOM）内的状态分布。状态的这种分布可以与状态的参考分布进行比较，从而允许活动与在生成参考分布状态时使用的活动进行比较。

8. 发明公开

EP2240891A2 PROCEDES DE MISE A JOUR ET D'APPRENTISSAGE D'UNE CARTE AUTO-ORGANISATRICE 有权
标题翻译：过程为一个自组织地图更新和学习
公开(公告)号：EP2240891A2
公开(公告)日：2010-10-20
申请号：EP08865257.3
申请日：2008-12-12
申请人： Universite Paris 13
发明人： BENNANI, Younes
IPC分类号： G06N3/08 , G06N1/00 , G06F15/18
CPC分类号： G06N3/082 , G06K9/6251 , G06N3/088
摘要： The invention relates to an updating method that comprises selecting the best winning neurone and the second best winning neurone, modifying the prototype vectors of the best winning neurone and of the neurones located around the best winning neurone in the direction of the vector of the training point (x(k)), determining the neighbouring neurones (N(u*)) of the best winning neurone(u*), and, if the second best winning neurone (u**) is part of the neighbouring neurones (N(u*)), increasing the valuation of the connection between the first and second best winning neurones. The updating method further comprises reducing the valuation of each connection between the first best winning neurone and the directly neighbouring neurones (N(u*)) different from the second best winning neurone (u**).

9. 发明授权

EP1038261B1 VISUALIZATION AND SELF-ORGANIZATION OF MULTIDIMENSIONAL DATA THROUGH EQUALIZED ORTHOGONAL MAPPING 有权
标题翻译：可视化和自组织多维数据 - 正交均衡的形象
公开(公告)号：EP1038261B1
公开(公告)日：2007-08-01
申请号：EP98963891.1
申请日：1998-12-14
申请人： Computer Associates Think, Inc.
发明人： PAO, Yoh-Han , MENG, Zhuo
IPC分类号： G06K9/66
CPC分类号： G06K9/6251 , G06K9/6232 , G06K9/6248
摘要： The subject system provides reduced-dimension mapping of pattern data. Mapping is applied through conventional single-hidden-layer feed-forward neural network with non-linear neurons. According to one aspect of the present invention, the system functions to equalize and orthogonalize lower dimensional output signals by reducing the covariance matrix of the output signals to the form of a diagonal matrix or constant times the identity matrix. The present invention allows for visualization of large bodies of complex multidimensional data in a relatively 'topologically correct' low-dimension approximation, to reduce randomness associated with other methods of similar purposes, and to keep the mapping computationally efficient at the same time.

10. 发明公开

EP1686494A1 SIMILAR PATTERN SEARCHING APPARATUS, METHOD OF SIMILAR PATTERN SEARCHING, PROGRAM FOR SIMILAR PATTERN SEARCHING, AND FRACTIONATION APPARATUS 审中-公开
标题翻译：设备，方法和程序来搜索类似的模式和分馏
公开(公告)号：EP1686494A1
公开(公告)日：2006-08-02
申请号：EP04818872.6
申请日：2004-11-12
申请人： National University Corporation Kochi University , A & T Corporation
发明人： KATAOKA, Hiromi, c/o Kochi Medical School Hospital
IPC分类号： G06F17/30 , G01N15/14 , G01N33/49
CPC分类号： G06K9/6251 , G01N2015/008 , G01N2015/1477 , G01N2015/1486 , G01N2015/1488 , G01N2015/1493 , G06F19/24 , G06K9/00147 , G06K9/6226
摘要： Respective components of a leukocyte particle size pattern that includes a plurality of cellular component fractions are separated by performing a mixture density approximation using an EM algorithm, and characteristic parameters of each fraction are clustered. A similarity search with attention paid to a distribution pattern of a cell group of interest is thereby executed. An algorithm capable of doing a highly accurate similarity search from general viewpoints such as a search for the respective cellular components of a leukocyte or a combination of the respective components is developed. In addition, information useful for a diagnosis is provided.
摘要翻译：白细胞粒径模式的各个部件没有包括细胞组分的级分的多元性通过执行使用算法来EM的混合物密度近似隔开，并且每个部分的特征参数进行聚类。相似性搜索与关注支付给感兴趣的细胞群的分布格局是由其执行。能够做到从一般视点的高度准确的相似性搜索的算法：如用于白细胞或respectivement组件的组合的respectivement细胞成分的搜索显影。此外，提供了一种用于诊断有用的信息。

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