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    • 4. 发明授权
    • System and method for motion-compensated compressed sensing for dynamic imaging
    • 用于动态成像的运动补偿压缩感测的系统和方法
    • US08520928B2
    • 2013-08-27
    • US13104255
    • 2011-05-10
    • Ali BilginYookyung KimMariappan S. NadarRajagopalan Sundaresan
    • Ali BilginYookyung KimMariappan S. NadarRajagopalan Sundaresan
    • G06K9/00
    • H04N19/577H04N19/61
    • A method for reconstructing a digital image from a set of measurements includes providing a previous image frame in a time series of measurements of an image signal and a current image frame in the time series, calculating an estimated motion vector for a spatial point and current time point between the previous and current image frames, calculating a motion compensated current image frame from the previous image frame, estimating a known support set of a sparse signal estimate of the motion compensated current image frame where the support set comprises indices of non-zero elements of the sparse signal estimate, calculating a sparse signal corresponding to the current image frame whose support contains a smallest number of new additions to the known support set while satisfying a data consistency constraint, and correcting the motion compensated current image frame image frame from the sparse signal.
    • 一种用于从一组测量重建数字图像的方法包括在时间序列中以图像信号和当前图像帧的时间序列测量的时间序列提供先前的图像帧,计算空间点和当前时间的估计的运动矢量 在先前图像帧和当前图像帧之间,从前一图像帧计算运动补偿当前图像帧,估计运动补偿当前图像帧的稀疏信号估计的已知支持集合,其中支持集合包括非零元素的索引 的稀疏信号估计,计算对应于当前图像帧的稀疏信号,其支持在满足数据一致性约束的同时包含对已知支持集合的最小数量的新加法,并且从稀疏信息校正运动补偿的当前图像帧图像帧 信号。
    • 5. 发明申请
    • SYSTEM AND METHOD FOR MOTION-COMPENSATED COMPRESSED SENSING FOR DYNAMIC IMAGING
    • 用于动态成像的运动补偿压缩感测的系统和方法
    • US20120008844A1
    • 2012-01-12
    • US13104255
    • 2011-05-10
    • Ali BilginYookyung KimMariappan S. NadarRajagopalan Sundaresan
    • Ali BilginYookyung KimMariappan S. NadarRajagopalan Sundaresan
    • G06K9/00
    • H04N19/577H04N19/61
    • A method for reconstructing a digital image from a set of measurements includes providing a previous image frame in a time series of measurements of an image signal and a current image frame in the time series, calculating an estimated motion vector for a spatial point and current time point between the previous and current image frames, calculating a motion compensated current image frame from the previous image frame, estimating a known support set of a sparse signal estimate of the motion compensated current image frame where the support set comprises indices of non-zero elements of the sparse signal estimate, calculating a sparse signal corresponding to the current image frame whose support contains a smallest number of new additions to the known support set while satisfying a data consistency constraint, and correcting the motion compensated current image frame image frame from the sparse signal.
    • 一种用于从一组测量重建数字图像的方法包括在时间序列中以图像信号和当前图像帧的时间序列测量的时间序列提供先前的图像帧,计算空间点和当前时间的估计的运动矢量 在先前图像帧和当前图像帧之间,从前一图像帧计算运动补偿当前图像帧,估计运动补偿当前图像帧的稀疏信号估计的已知支持集合,其中支持集合包括非零元素的索引 的稀疏信号估计,计算对应于当前图像帧的稀疏信号,其支持在满足数据一致性约束的同时包含对已知支持集合的最小数量的新加法,并且从稀疏信息校正运动补偿的当前图像帧图像帧 信号。
    • 7. 发明授权
    • Short text language detection using geographic information
    • 使用地理信息的短文本语言检测
    • US08548797B2
    • 2013-10-01
    • US12262145
    • 2008-10-30
    • Yookyung KimShuang GuoXian Xiang HuXin Li
    • Yookyung KimShuang GuoXian Xiang HuXin Li
    • G06F17/20G06F17/28G06F17/27G06F17/21G10L21/00
    • G06F17/275
    • A content-providing entity receives a relatively short text from a user and attempts to determine, automatically, based on that short text (and on other available clues), a language that the user can read and understand. The content-providing entity may then provide, to the user, documents that are written in the determined language. The content-providing entity may determine a language of the input text based on several factors in combination: (a) the service provider's “market,” which is determined based on at least a portion of the URL of the Internet site to which the user directed his browser; (b) the user's “region,” which is determined based on the source Internet Protocol (IP) address of the IP packets that the user sends to the Internet site; (c) the “script” in which the short user-entered text is written; and (d) a statistical analysis of the frequency of the characters present in the short user-entered text.
    • 内容提供实体从用户接收相对短的文本,并尝试基于该短文本(以及其他可用线索)来确定用户可以阅读和理解的语言。 然后,内容提供实体可以向用户提供以确定的语言书写的文档。 内容提供实体可以基于以下几个因素来确定输入文本的语言:(a)服务提供商的“市场”,其基于用户所在的因特网站点的URL的至少一部分来确定 指导他的浏览器 (b)基于用户发送到因特网站点的IP分组的源IP地址确定用户的“区域”; (c)写入短的用户输入的文本的“脚本”; 和(d)对短用户输入文本中存在的字符的频率的统计分析。
    • 8. 发明申请
    • SHORT TEXT LANGUAGE DETECTION USING GEOGRAPHIC INFORMATION
    • 使用地理信息的短文本语言检测
    • US20100114559A1
    • 2010-05-06
    • US12262145
    • 2008-10-30
    • Yookyung KimShuang GuoXian Xiang HuXin Li
    • Yookyung KimShuang GuoXian Xiang HuXin Li
    • G06F17/20
    • G06F17/275
    • A content-providing entity receives a relatively short text from a user and attempts to determine, automatically, based on that short text (and on other available clues), a language that the user can read and understand. The content-providing entity may then provide, to the user, documents that are written in the determined language. The content-providing entity may determine a language of the input text based on several factors in combination: (a) the service provider's “market,” which is determined based on at least a portion of the URL of the Internet site to which the user directed his browser; (b) the user's “region,” which is determined based on the source Internet Protocol (IP) address of the IP packets that the user sends to the Internet site; (c) the “script” in which the short user-entered text is written; and (d) a statistical analysis of the frequency of the characters present in the short user-entered text.
    • 内容提供实体从用户接收相对短的文本,并尝试基于该短文本(以及其他可用的线索)来确定用户可以阅读和理解的语言。 然后,内容提供实体可以向用户提供以确定的语言书写的文档。 内容提供实体可以基于以下几个因素来确定输入文本的语言:(a)服务提供商的“市场”,其基于用户所在的因特网站点的URL的至少一部分来确定 指导他的浏览器 (b)基于用户发送到因特网站点的IP分组的源IP地址确定用户的“区域”; (c)写入短的用户输入的文本的“脚本”; 和(d)对短用户输入文本中存在的字符的频率的统计分析。
    • 9. 发明申请
    • Chunk-based statistical machine translation system
    • 基于块的统计机器翻译系统
    • US20080154577A1
    • 2008-06-26
    • US11645926
    • 2006-12-26
    • Yookyung KimJun HuangYoussef Billawala
    • Yookyung KimJun HuangYoussef Billawala
    • G06F17/28
    • G06F17/2827G06F17/2775
    • Traditional statistical machine translation systems learn all information from a sentence aligned parallel text and are known to have problems translating between structurally diverse languages. To overcome this limitation, the present invention introduces two-level training, which incorporates syntactic chunking into statistical translation. A chunk-alignment step is inserted between the sentence-level and word-level training, which allows differing training for these two sources of information in order to learn lexical properties from the aligned chunks and learn structural properties from chunk sequences. The system consists of a linguistic processing step, two level training, and a decoding step which combines chunk translations of multiple sources and multiple language models.
    • 传统的统计机器翻译系统从句子对齐的并行文本中学习所有信息,并且已知在不同结构语言之间翻译有问题。 为了克服这个限制,本发明引入了将句法分块结合到统计翻译中的两级训练。 在句子级和词级训练之间插入块对齐步骤,其允许针对这两个信息源的不同训练,以便从对齐的块学习词汇属性并从块序列学习结构特性。 该系统由语言处理步骤,两级训练和解码步骤组成,该步骤结合了多个来源和多种语言模型的块转换。
    • 10. 发明授权
    • Infinite browse
    • 无限浏览
    • US08600979B2
    • 2013-12-03
    • US12825304
    • 2010-06-28
    • Yookyung KimHongjian ZhaoXin LiAlexandra LevichTom ChiMing SuiYihong ZhaoMarc Davis
    • Yookyung KimHongjian ZhaoXin LiAlexandra LevichTom ChiMing SuiYihong ZhaoMarc Davis
    • G06F7/00
    • G06F17/3089G06F17/30522
    • An online article is enhanced by displaying, in association with the article, supplemental content that includes entities that are extracted from the article and/or entities that are related to entities that are extracted from the article. The supplemental content further includes information about each of the entities. The information about an entity may be obtained by searching for the entity in one or more searchable repositories of data. For example, the supplemental content may include, for each entity, video, image, web, and/or news search results. The supplemental content may further include information such as stock quotes, abstracts, maps, scores, and so on. The entities are selected using a variety of analyses and ranking techniques based on contextual factors such as user-specific information, time-sensitive popularity trends, grammatical features, search result quality, and so on. The entities may further be selected for purposes such as generating ad-based revenue.
    • 通过与文章相关联地显示包括从文章中提取的实体和/或与从文章中提取的实体相关的实体的补充内容来增强在线文章。 补充内容还包括关于每个实体的信息。 可以通过在一个或多个可搜索的数据库中搜索实体来获得关于实体的信息。 例如,对于每个实体,补充内容可以包括视频,图像,网络和/或新闻搜索结果。 补充内容还可以包括股票报价,摘要,地图,分数等信息。 使用各种基于上下文因素的分析和排序技术来选择实体,例如用户特定信息,时间敏感的人气趋势,语法特征,搜索结果质量等。 可以进一步选择实体,例如生成基于广告的收入。