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81.发明授权Method and apparatus for biologically inspired autonomous infrastructure monitoring 有权用于生物灵感的自主式基础设施监测的方法和装置公开(公告)号：US09537954B2
公开(公告)日：2017-01-03
申请号：US14716852
申请日：2015-05-19
申请人： EpiSys Science, Inc.
IPC分类号： G07C5/02 , H04L29/08 , H04W76/04 , H04W72/04 , H04W24/10 , H04W4/02 , H04W76/02 , G07C5/08 , H04W40/24 , H04W84/18 , H04W84/00 , G05D1/00 , G06K9/62
CPC分类号： H04L67/12 , G05D1/00 , G05D1/104 , G06K9/00664 , G06K9/6284 , G06K9/6296 , G06K9/6297 , G07C5/02 , G07C5/08 , H04W4/021 , H04W4/023 , H04W24/10 , H04W40/248 , H04W72/0406 , H04W76/11 , H04W76/25 , H04W84/005 , H04W84/18
摘要： A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.
摘要翻译： 提供了一种方法和装置，用于自主地检测和报告自主移动节点的动作中的异常，或者对于运营商的自治移动节点群的行为。 由于各种故障或外部影响（例如自然天气现象，敌人威胁），自主移动节点可能会经历异常或意外情况。 在训练阶段期间，可以在正常情况下执行动作或行为时，从自主移动节点或节点群的一个或多个传感器接收的测量数据建立预测模型和结构化模型。 预测模型预测行动或行为的预期结果，结构化模型有助于量化学习动作或行为与当前观察到的情境的相似性。 基于测量数据，适用的模型可以用于动作或行为中异常检测的动作或行为。
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公开(公告)号：US09478201B1
公开(公告)日：2016-10-25
申请号：US15027248
申请日：2014-12-24
申请人： TONARA LTD.
发明人： Evgeni Begelfor , Michael Zakai , Ron Regev
CPC分类号： G10H1/0033 , G06K9/00 , G06K9/6297 , G10G1/00 , G10H1/18 , G10H2210/051 , G10H2210/071 , G10H2210/081 , G10H2220/455 , G10H2250/015
摘要： Music recognition is carried out by accepting a musical score of musical elements in a digital format, transforming the digital format into a composite musical data object that models the musical score, defining the key signatures in the composite musical data object probabilistically, computing start times to play musical elements in respective measures of the composite musical data object without regard to rhythmic values of other musical elements in the respective measures, and generating an output including the defined key signatures and computed start times.
摘要翻译： 通过以数字格式接受音乐元素的乐谱来进行音乐识别，将数字格式变换为对乐谱进行建模的综合音乐数据对象，概率地定义复合音乐数据对象中的键签名，计算开始时间 在各个度量中不考虑其他音乐元素的节奏值，并且生成包括所定义的键签名和计算的开始时间的输出，在复合音乐数据对象的各个度量中播放音乐元素。
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公开(公告)号：US09390380B2
公开(公告)日：2016-07-12
申请号：US13976744
申请日：2013-03-15
申请人： Intel Corporation
发明人： Chuck Evans
CPC分类号： G06N99/005 , G06K9/00335 , G06K9/6256 , G06K9/6272 , G06K9/6297 , G06N7/005 , G10L15/14 , G10L15/142
摘要： Systems and methods may provide for partitioning a plurality of training samples into a first sequential list of centroids, removing one or more repeating centroids in the first sequential list of centroids to obtain a first reduced list of centroids and generating a set of Hidden Markov Model (HMM) parameters based on the first reduced list of centroids. Additionally, a plurality of detection samples may be partitioned into a second sequential list of centroids, wherein one or more repeating centroids in the second sequential list of centroids may be removed to obtain a second reduced list of centroids. The second reduced list of centroids may be used to determine a match probability for the plurality of detection samples against the set of HMM parameters. In one example, the reduced lists of centroids lack temporal variability.
摘要翻译： 系统和方法可以提供将多个训练样本划分成质心的第一顺序列表，去除第一顺序的质心列表中的一个或多个重复质心，以获得质心的第一简化列表并生成一组隐马尔可夫模型（ HMM）参数基于第一个减少的重心列表。 另外，多个检测样本可以被划分成质心的第二顺序列表，其中质心的第二顺序列表中的一个或多个重复质心可以被去除以获得第二缩小的质心列表。 质心的第二减少列表可用于确定针对所述一组HMM参数的多个检测样本的匹配概率。 在一个示例中，减少的质心列表缺少时间变异性。
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84.发明申请公开(公告)号：US20160188964A1
公开(公告)日：2016-06-30
申请号：US14986344
申请日：2015-12-31
发明人： Azhar Quddus , Xiaoming Nan , Naimul Khan , Ling Guan
CPC分类号： G06K9/00288 , G06K9/00 , G06K9/00899 , G06K9/6297
摘要： The method includes a dictionary including a target collection defined by images that are known with a defined level of certainty to include a subject and an imposter collection defined by images of individuals other than the subject. In the method, images of an area are captured over a period of time. In respect of each image: a matching calculation is carried out, based upon a comparison of the image captured with the images in the dictionary to result in a measure of confidence that the subject is in the area; and an inference determination is made to replace one of the target collection images with a further image that is known with the defined level of certainty, the determination being a function of the measure of confidence resultant from the captured image, the measure resultant from one or more previously captured images and the associated capture times.
摘要翻译： 该方法包括字典，其包括由具有确定的确定水平已知的图像定义的目标集合，以包括被摄体和由该受试者以外的个体的图像定义的冒名顶替者收藏。 在该方法中，在一段时间内捕获区域的图像。 对于每个图像：基于与字典中的图像捕获的图像的比较来执行匹配计算，以得到对象在该区域中的置信度的度量; 并且进行推断确定以用确定的确定水平已知的另外的图像来替换目标收集图像中的一个，所述确定是从所捕获的图像产生的置信度的函数的函数， 更先前捕获的图像和相关的捕获时间。
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85.发明授权Method and system for recognizing and assessing surgical procedures from video 有权从视频识别和评估外科手术的方法和系统公开(公告)号：US09171477B2
公开(公告)日：2015-10-27
申请号：US14223679
申请日：2014-03-24
发明人： Jiebo Luo , Junhuan Zhu , Yousuf Mohamed Khalifa
CPC分类号： G09B5/00 , G06K9/00597 , G06K9/6297 , G06K2209/057
摘要： A Method and System For Recognizing and Assessing Surgical Procedures from a video or series of still images is described. Evaluation of surgical techniques of residents learning skills in areas such as cataract surgery is an important aspect of the learning process. The use of videos has become common in such evaluations, but is a time consuming manual process. The present invention increases the efficiency and speed of the surgical technique evaluation process by identifying and saving only information that is relevant to the evaluation process. Using image processing techniques of the present invention, an anatomic structure of a surgical procedure is located on a video, timing of predefined surgical stages is determined, and measurements are taken from frames of the predefined surgical stages to allow the performance of a surgeon to be assessed in an automated and efficient manner.
摘要翻译： 描述了从视频或一系列静止图像中识别和评估外科手术的方法和系统。 评估白内障手术领域居民学习技巧的手术技术是学习过程的一个重要方面。 视频的使用在这样的评估中变得很常见，但是这是一个耗时的手动过程。 本发明通过仅识别和保存与评估过程相关的信息来提高手术技术评估过程的效率和速度。 使用本发明的图像处理技术，将外科手术的解剖结构定位在视频上，确定预定手术阶段的时间，并且从预定义的手术阶段的帧中进行测量，以允许外科医生的表现为 以自动化和高效的方式进行评估。
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公开(公告)号：US20150170005A1
公开(公告)日：2015-06-18
申请号：US14107520
申请日：2013-12-16
发明人： Scott Cohen , Brian Lynn Price , Ejaz Ahmed
CPC分类号： G06F17/30825 , G06F17/30247 , G06F17/30277 , G06F17/3079 , G06K9/00684 , G06K9/6215 , G06K9/6256 , G06K9/6297 , G06T7/11 , G06T7/143 , G06T7/194 , G06T11/60 , G06T2200/24 , G06T2207/20076 , G06T2207/20092
摘要： Techniques are disclosed herein that enable digital images to be segmented based on a user's semantic input. In other words, given an input image of a person walking a dog adjacent to a tree, a user can simply provide the semantic input “dog” and the system will segment the dog from the other elements in the image. If the user provides other semantic input, such as “person” or “tree”, the system will segment the person or the tree, respectively, from the same image. Using semantic input advantageously eliminates any need for a user to directly interact with the input image through a tedious process of painting brush strokes, tracing boundaries, clicking target points, and/or drawing bounding boxes. Thus semantic input represents an easier and more intuitive way for users to interact with an image segmentation interface, thereby enabling novice users to take advantage of advanced image segmentation techniques.
摘要翻译： 本文公开了使得能够基于用户的语义输入来分割数字图像的技术。 换句话说，给予在与树相邻的人行走的人的输入图像，用户可以简单地提供语义输入“狗”，并且系统将从图像中的其他元素分割狗。 如果用户提供诸如“人”或“树”的其他语义输入，则系统将分别从同一图像中分割人或树。 使用语义输入有利地消除了用户通过绘画画笔笔画，跟踪边界，点击目标点和/或绘制边界框的繁琐过程直接与输入图像交互的任何需要。 因此，语义输入表示用户与图像分割界面交互的更简单和更直观的方式，从而使新手用户能够利用高级图像分割技术。
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公开(公告)号：US09025866B2
公开(公告)日：2015-05-05
申请号：US13929651
申请日：2013-06-27
发明人： Ce Liu
CPC分类号： G06K9/6229 , G06K9/00577 , G06K9/4671 , G06K9/6297
摘要： A method of operating a computer system to perform material recognition based on multiple features extracted from an image is described. A combination of low-level features extracted directly from the image and multiple novel mid-level features extracted from transformed versions of the image are selected and used to assign a material category to a single image. The novel mid-level features include non-reflectance based features such as the micro-texture features micro-jet and micro-SIFT and the shape feature curvature, and reflectance-based features including edge slice and edge ribbon. An augmented Latent Dirichlet Allocation (LDA) model is provided as an exemplary Bayesian framework for selecting a subset of features useful for material recognition of objects in an image.
摘要翻译： 描述了基于从图像提取的多个特征来操作计算机系统以执行材料识别的方法。 选择直接从图像中提取的低级特征和从图像的变换版本提取的多个新颖的中级特征的组合，并用于将材料类别分配给单个图像。 新颖的中级功能包括基于非反射率的特征，如微观纹理特征微射流和微SIFT以及形状特征曲率，以及基于反射率的特征，包括边缘切片和边缘带。 提供增强的潜在狄利克雷分配（LDA）模型作为示例性贝叶斯框架，用于选择对于图像中的对象的材料识别有用的特征的子集。
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88.发明授权Computer aided diagnostic system incorporating appearance analysis for diagnosing malignant lung nodules 有权包括诊断恶性肺结节的外观分析的计算机辅助诊断系统公开(公告)号：US09014456B2
公开(公告)日：2015-04-21
申请号：US13368977
申请日：2012-02-08
申请人： Ayman S. El-Baz
发明人： Ayman S. El-Baz
CPC分类号： G06T7/0014 , G06K9/621 , G06K9/6297 , G06K2209/051 , G06T2207/10081 , G06T2207/20081 , G06T2207/30064
摘要： A computer aided diagnostic system and automated method diagnose lung cancer through modeling and analyzing the visual appearance of pulmonary nodules. A learned appearance model used in such analysis describes the appearance of pulmonary nodules in terms of voxel-wise conditional Gibbs energies for a generic rotation and translation invariant second-order Markov-Gibbs random field (MGRF) model of malignant nodules with analytically estimated characteristic voxel neighborhoods and potentials.
摘要翻译： 计算机辅助诊断系统和自动化方法通过建模和分析肺结节的视觉外观来诊断肺癌。 在这样的分析中使用的学习外观模型描述了用于具有分析估计的特征体素的恶性结节的通用旋转和平移不变二阶马尔科夫吉布斯随机场（MGRF）模型的体素条件吉布斯能量的肺结节的出现 社区和潜力。
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89.发明授权Method and system for ablation catheter and circumferential mapping catheter tracking in fluoroscopic images 有权消融导管的方法和系统以及荧光镜图像中的周向映射导管跟踪公开(公告)号：US09002436B2
公开(公告)日：2015-04-07
申请号：US13622404
申请日：2012-09-19
发明人： Wen Wu , Terrence Chen , Norbert Strobel , Dorin Comaniciu
CPC分类号： G06K9/6297 , A61B6/12 , A61B6/487 , A61B18/1492 , A61B34/20 , A61B2018/00315 , A61B2018/00577 , A61B2034/102 , A61B2034/2065 , A61B2090/376 , G06K2209/057 , G06T7/248 , G06T7/277 , G06T2207/10121 , G06T2207/20081 , G06T2207/20101 , G06T2207/30021
摘要： A method and system for tracking an ablation catheter and a circumferential mapping catheter in a fluoroscopic image sequence is disclosed. Catheter electrode models for the ablation catheter and the circumferential mapping catheter are initialized in a first frame of a fluoroscopic image sequence based on user inputs. The catheter electrode models for the ablation catheter and the circumferential mapping catheter are then tracked in each remaining frame of the fluoroscopic image sequence. In each remaining frame, candidates of catheter landmarks such as the catheter tip, electrodes and body points are detected for the ablation catheter and the circumferential mapping catheter, tracking hypotheses for the catheter electrode models are generated, and for each of the ablation catheter and the circumferential mapping catheter, the catheter electrode model having the highest probability score is selected from the generated tracking hypotheses.
摘要翻译： 公开了一种用于跟踪消融导管和透视图像序列中的周向映射导管的方法和系统。 基于用户输入，在荧光镜图像序列的第一帧中初始化用于消融导管和周向映射导管的导管电极模型。 然后在荧光镜图像序列的每个剩余帧中跟踪用于消融导管和周向映射导管的导管电极模型。 在每个剩余的帧中，针对消融导管和周向映射导管检测诸如导管尖端，电极和身体点的导管标记的候选物，产生用于导管电极模型的跟踪假设，并且对于消融导管和 从产生的跟踪假设中选择具有最高概率得分的导管电极模型。
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公开(公告)号：US08917907B2
公开(公告)日：2014-12-23
申请号：US13406011
申请日：2012-02-27
申请人： Jinjun Wang , Jing Xiao
发明人： Jinjun Wang , Jing Xiao
CPC分类号： G06K9/00765 , G06K9/00335 , G06K9/6297
摘要： Aspects of the present invention include systems and methods for segmentation and recognition of action primitives. In embodiments, a framework, referred to as the Continuous Linear Dynamic System (CLDS), comprises two sets of Linear Dynamic System (LDS) models, one to model the dynamics of individual primitive actions and the other to model the transitions between actions. In embodiments, the inference process estimates the best decomposition of the whole sequence into continuous alternating between the two set of models, using an approximate Viterbi algorithm. In this way, both action type and action boundary may be accurately recognized.
摘要翻译： 本发明的方面包括用于分割和识别动作原语的系统和方法。 在实施例中，被称为连续线性动态系统（CLDS）的框架包括两组线性动态系统（LDS）模型，其中一个模型用于对各个原始动作的动力学进行建模，另一组模型对动作之间的转换进行建模。 在实施例中，推理过程使用近似维特比算法来估计整个序列的最佳分解到两组模型之间的连续交替。 以这种方式，可以准确地识别动作类型和动作边界。
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