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    Evaluation of a technology library for use in an electronic design automation system that converts the technology library into non-linear, gain-based models for estimating circuit delay
    11.
    发明授权
    Evaluation of a technology library for use in an electronic design automation system that converts the technology library into non-linear, gain-based models for estimating circuit delay 有权
    评估用于电子设计自动化系统的技术库，将技术库转换为非线性增益型估计电路延迟模型

    公开(公告)号：US06446240B1

    公开(公告)日：2002-09-03

    申请号：US09451467

    申请日：1999-11-30

    申请人： Mahesh Iyer ,  Ashish Kapoor

    发明人： Mahesh Iyer ,  Ashish Kapoor

    IPC分类号： G06F1750

    CPC分类号： G06F17/5022

    摘要： An evaluation system for evaluating the suitability of a target technology library for use with an electronic design automation system that converts the target technology library into a scalable library having non-linear, gain-based delay models for estimating circuit delay. After a library analysis process executes, an internal scalable library is generated having a scalable cell model for each functional cell class of the target technology library. Internal characteristics of the scalable library are analyzed to determine whether or not the target technology library is suitable for generating a suitable scalable library. Suitable scalable libraries are used for gain-based structuring and mapping processes. The library evaluation processes uses several metrics to determine the suitability the target technology library. The first metric is the number of sizes metric and the second metric is the size consistency metric. The number of sizes metric is computed with respect to subsets (e.g., basic set and extended set) of the scalable cells identified within the scalable library. The number of sizes metric determines whether or not there are sufficient numbers of discrete cells within the cell clusters of the subsets. The size consistency metric examines the input pin capacitance ratios and the delay error amounts for discrete cells of the scalable library. An evaluation report is then compiled using the above metric information to grade library suitability.

    摘要翻译： 用于评估目标技术库与电子设计自动化系统的适用性的评估系统，其将目标技术库转换成具有用于估计电路延迟的非线性增益型延迟模型的可扩展库。 在执行库分析过程之后，生成具有针对目标技术库的每个功能单元类的可缩放单元模型的内部可伸缩库。 分析可扩展库的内部特性，以确定目标技术库是否适于生成合适的可扩展库。 适用的可扩展库用于基于增益的结构化和映射过程。 图书馆评估过程使用多个指标来确定目标技术库的适用性。 第一个度量是度量的数量，第二个度量是大小一致性指标。 针对在可伸缩库中标识的可缩放单元的子集（例如，基本集合和扩展集合）计算尺寸度量的数量。 大小度量的数量确定在子集的小区簇内是否存在足够数量的离散小区。 尺寸一致性度量检查输入引脚电容比和可伸缩库的离散单元的延迟误差量。 然后使用上述度量信息编译评估报告，以评估图书馆的适用性。

    Interactive concept learning in image search
    12.
    发明授权
    Interactive concept learning in image search 有权
    图像搜索中的互动概念学习

    公开(公告)号：US09008446B2

    公开(公告)日：2015-04-14

    申请号：US13429342

    申请日：2012-03-24

    申请人： Desney S. Tan ,  Ashish Kapoor ,  Simon A. J. Winder ,  James A. Fogarty

    发明人： Desney S. Tan ,  Ashish Kapoor ,  Simon A. J. Winder ,  James A. Fogarty

    IPC分类号： G06K9/62 ,  G06F17/30

    CPC分类号： G06F17/30247 ,  G06K9/6215

    摘要： An interactive concept learning image search technique that allows end-users to quickly create their own rules for re-ranking images based on the image characteristics of the images. The image characteristics can include visual characteristics as well as semantic features or characteristics, or may include a combination of both. End-users can then rank or re-rank any current or future image search results according to their rule or rules. End-users provide examples of images each rule should match and examples of images the rule should reject. The technique learns the common image characteristics of the examples, and any current or future image search results can then be ranked or re-ranked according to the learned rules.

    摘要翻译： 一种交互式概念学习图像搜索技术，允许最终用户基于图像的图像特征快速创建自己的重新排序图像的规则。 图像特征可以包括视觉特征以及语义特征或特征，或者可以包括两者的组合。 然后，最终用户可以根据其规则或规则对当前或将来的图像搜索结果进行排名或重新排序。 最终用户提供每个规则应该匹配的图像的示例以及规则应该拒绝的图像的示例。 该技术学习示例的常见图像特征，然后可以根据学习的规则对任何当前或将来的图像搜索结果进行排名或重新排序。

    Non-linguistic signal detection and feedback
    13.
    发明授权
    Non-linguistic signal detection and feedback 有权
    非语言信号检测和反馈

    公开(公告)号：US08963987B2

    公开(公告)日：2015-02-24

    申请号：US12789142

    申请日：2010-05-27

    申请人： Byungki Byun ,  Philip A. Chou ,  Mary P. Czerwinski ,  Ashish Kapoor ,  Bongshin Lee

    发明人： Byungki Byun ,  Philip A. Chou ,  Mary P. Czerwinski ,  Ashish Kapoor ,  Bongshin Lee

    IPC分类号： H04N7/14 ,  H04N7/15

    CPC分类号： H04N7/15 ,  H04N7/147

    摘要： Non-linguistic signal information relating to one or more participants to an interaction may be determined using communication data received from the one or more participants. Feedback can be provided based on the determined non-linguistic signals. The participants may be given an opportunity to opt in to having their non-linguistic signal information collected, and may be provided complete control over how their information is shared or used.

    摘要翻译： 可以使用从一个或多个参与者接收的通信数据来确定与交互的一个或多个参与者有关的非语言信号信息。 可以基于确定的非语言信号提供反馈。 参与者可能有机会选择收集其非语言信号信息，并且可以完全控制他们的信息如何共享或使用。

    Image quality assessment
    14.
    发明授权
    Image quality assessment 有权

    公开(公告)号：US08494283B2

    公开(公告)日：2013-07-23

    申请号：US12975026

    申请日：2010-12-21

    申请人： Neel Joshi ,  Ashish Kapoor ,  Huixuan Tang

    发明人： Neel Joshi ,  Ashish Kapoor ,  Huixuan Tang

    IPC分类号： G06K9/46

    CPC分类号： G06K9/46 ,  G06K9/036 ,  G06K9/6253

    摘要： Methods and systems for image quality assessment are disclosed. A method includes accessing an image, identifying features of the image, assessing the features and generating subjective scores for the features based upon a mapping of the features to the subjective scores and based on the subjective scores, generating an image quality score. Access is provided to the image quality score.

    Interactive visualization for generating ensemble classifiers
    16.
    发明授权
    Interactive visualization for generating ensemble classifiers 有权
    用于生成综合分类器的交互式可视化

    公开(公告)号：US08306940B2

    公开(公告)日：2012-11-06

    申请号：US12408663

    申请日：2009-03-20

    申请人： Bongshin Lee ,  Ashish Kapoor ,  Desney S. Tan ,  Justin Talbot

    发明人： Bongshin Lee ,  Ashish Kapoor ,  Desney S. Tan ,  Justin Talbot

    IPC分类号： G06F15/18 ,  G06F17/00 ,  G06N5/04

    CPC分类号： G06N99/005

    摘要： A real-time visual feedback ensemble classifier generator and method for interactively generating an optimal ensemble classifier using a user interface. Embodiments of the real-time visual feedback ensemble classifier generator and method use a weight adjustment operation and a partitioning operation in the interactive generation process. In addition, the generator and method include a user interface that provides real-time visual feedback to a user so that the user can see how the weight adjustment and partitioning operation affect the overall accuracy of the ensemble classifier. Using the user interface and the interactive controls available on the user interface, a user can iteratively use one or both of the weigh adjustment operation and partitioning operation to generate an optimized ensemble classifier.

    摘要翻译： 一种实时视觉反馈综合分类器生成器和方法，用于使用用户界面交互式生成最佳集合分类器。 实时视觉反馈综合分类器发生器和方法的实施例在交互式生成过程中使用权重调整操作和分割操作。 此外，发生器和方法包括向用户提供实时视觉反馈的用户界面，使得用户可以看到权重调整和分割操作如何影响整体分类器的整体精度。 使用用户界面上的用户界面和交互式控件，用户可以迭代地使用权重调整操作和分区操作中的一个或两者来生成优化的整体分类器。

    Palette-based classifying and synthesizing of auditory information
    18.
    发明授权
    Palette-based classifying and synthesizing of auditory information 有权
    基于调色板的听觉信息分类与综合

    公开(公告)号：US07634405B2

    公开(公告)日：2009-12-15

    申请号：US11041827

    申请日：2005-01-24

    申请人： Sumit Basu ,  Nebojsa Jojic ,  Ashish Kapoor

    发明人： Sumit Basu ,  Nebojsa Jojic ,  Ashish Kapoor

    IPC分类号： G10L15/06 ,  G10L15/00 ,  G10L17/00 ,  G10L13/00

    CPC分类号： G10L25/48

    摘要： The subject invention leverages spectral “palettes” or representations of an input sequence to provide recognition and/or synthesizing of a class of data. The class can include, but is not limited to, individual events, distributions of events, and/or environments relating to the input sequence. The representations are compressed versions of the data that utilize a substantially smaller amount of system resources to store and/or manipulate. Segments of the palettes are employed to facilitate in reconstruction of an event occurring in the input sequence. This provides an efficient means to recognize events, even when they occur in complex environments. The palettes themselves are constructed or “trained” utilizing any number of data compression techniques such as, for example, epitomes, vector quantization, and/or Huffman codes and the like.

    摘要翻译： 本发明利用光谱“调色板”或输入序列的表示来提供一类数据的识别和/或合成。 该类可以包括但不限于单个事件，事件分布和/或与输入序列有关的环境。 这些表示是利用相当少量的系统资源来存储和/或操纵的数据的压缩版本。 调色板的片段被用于促进在输入序列中发生的事件的重构。 这提供了一种识别事件的有效方法，即使它们发生在复杂环境中。 使用任何数量的数据压缩技术（例如，缩略图，矢量量化和/或霍夫曼码等）构建或“训练”调色板本身。

    AUTOMATED CALL CLASSIFICATION AND PRIORITIZATION
    19.
    发明申请
    AUTOMATED CALL CLASSIFICATION AND PRIORITIZATION 审中-公开
    自动呼叫分类和优先

    公开(公告)号：US20090006085A1

    公开(公告)日：2009-01-01

    申请号：US11770921

    申请日：2007-06-29

    申请人： Eric J. Horvitz ,  Ashish Kapoor ,  Sumit Basu

    发明人： Eric J. Horvitz ,  Ashish Kapoor ,  Sumit Basu

    IPC分类号： G10L19/12

    CPC分类号： G10L17/26 ,  G10L15/26 ,  G10L17/00

    摘要： An automated voice message or caller prioritization system that extracts words, prosody, and/or metadata from a voice input. The data extracted is classified with a statistical classifier into groups of interest. These groups could indicate the likelihood that a call is urgent versus nonurgent, from someone the user knows well versus someone that the user only knows casually or not at all, from someone using a mobile phone versus a landline, or a business call versus a personal calls. The system then can determine an action based on results of the groups, including the display of likely category labels on the message. Call handling and display actions can be defined by user preferences.

    摘要翻译： 自动语音消息或呼叫者优先级系统，其从语音输入中提取单词，韵律和/或元数据。 提取的数据用统计分类器分类为感兴趣的组。 这些群体可能表明呼叫紧急与非营销的可能性，用户知道的用户与用户只是随便知道的人，从使用移动电话的人士到固定电话，或商业电话与个人 电话。 然后，系统可以基于组的结果来确定动作，包括在消息上显示可能的类别标签。 呼叫处理和显示操作可以由用户偏好来定义。