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公开(公告)号：US20090327230A1
公开(公告)日：2009-12-31
申请号：US12147574
申请日：2008-06-27
IPC分类号： G06F17/30
CPC分类号： G06F16/40
摘要： Structured and/or unstructured data is processed with the aid of a data model. The data model provides a conceptual description of source content that can be generated or otherwise modified automatically as a function of data, models, and/or structure associated with the data. Both structured and unstructured data can be viewed in terms of high-level content rather than a lower level physical model. Among other things, this view can be employed to aid search as well as data sharing.
摘要翻译： 借助于数据模型处理结构化和/或非结构化数据。 数据模型提供了可以根据与数据相关联的数据，模型和/或结构的函数自动生成或以其他方式修改的源内容的概念描述。 结构化和非结构化数据都可以从高级内容而不是较低级别的物理模型来查看。 除此之外，这种观点可以用于帮助搜索和数据共享。
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62.发明授权公开(公告)号：US07548892B2
公开(公告)日：2009-06-16
申请号：US11748474
申请日：2007-05-14
CPC分类号： G06N99/005 , G06N3/08
摘要： A system and method for processing machine learning techniques (such as neural networks) and other non-graphics applications using a graphics processing unit (GPU) to accelerate and optimize the processing. The system and method transfers an architecture that can be used for a wide variety of machine learning techniques from the CPU to the GPU. The transfer of processing to the GPU is accomplished using several novel techniques that overcome the limitations and work well within the framework of the GPU architecture. With these limitations overcome, machine learning techniques are particularly well suited for processing on the GPU because the GPU is typically much more powerful than the typical CPU. Moreover, similar to graphics processing, processing of machine learning techniques involves problems with solving non-trivial solutions and large amounts of data.
摘要翻译： 一种用于处理机器学习技术（例如神经网络）和使用图形处理单元（GPU）来加速和优化处理的其他非图形应用的系统和方法。 该系统和方法传输一种可用于从CPU到GPU的各种机器学习技术的架构。 处理到GPU的转移是通过克服这些限制并在GPU架构的框架内工作良好的几种新技术实现的。 由于克服了这些限制，机器学习技术特别适用于GPU上的处理，因为GPU通常比典型的CPU功能更强大。 此外，类似于图形处理，机器学习技术的处理涉及解决非平凡解决方案和大量数据的问题。
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公开(公告)号：US07376275B2
公开(公告)日：2008-05-20
申请号：US11198562
申请日：2005-08-05
IPC分类号： G06K9/68
CPC分类号： G06K9/00442 , G06K9/46 , G06K9/6202 , G06K2209/01
摘要： Systems and methods for performing clustering of a document image are disclosed. A property of an extracted mark from a document is compared to the properties of the existing clusters. If the property of the mark fails to match any of the properties of the existing clusters, the mark is added as a new cluster to the existing cluster. One property that can be utilized is x size and y size, which is the width and height, of the existing clusters. Another property that can be employed is ink size, which refers to the ratio of black pixels to total pixels in a cluster. Yet another property that can be utilized is a reduced mark or image, which is a pixel size reduced version the bitmap of the mark and/or cluster. The above properties can be employed to identify mismatches and reduce the number of bit by bit comparisons performed.
摘要翻译： 公开了用于执行文档图像的聚类的系统和方法。 将来自文档的提取标记的属性与现有集群的属性进行比较。 如果标记的属性无法匹配现有集群的任何属性，则该标记作为新集群添加到现有集群。 可以使用的一个属性是x size和y size，这是现有集群的宽度和高度。 可以使用的另一个属性是墨水大小，其指的是群集中黑色像素与总像素的比例。 可以使用的另一个属性是缩小的标记或图像，其是像素尺寸缩小版本的标记和/或集群的位图。 可以采用上述特性来识别不匹配并减少进行的逐比较比较。
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64.发明授权公开(公告)号：US07317838B2
公开(公告)日：2008-01-08
申请号：US11734299
申请日：2007-04-12
CPC分类号： G06K9/6202 , G06T9/001 , H04N1/4115 , H04N19/97
摘要： A system and method facilitating compression of bi-level images with explicit representation of ink clusters is provided. The present invention includes a cluster shape estimator that analyzes connected component information, extracts clusters and stores the cluster in a global dictionary, a page dictionary or a store of unclustered shapes. A bitmap estimation from clusters component determines dictionary positions for clusters stored in the global dictionary which are then encoded. A cluster position estimator determines page positions of clusters of the global dictionary and/or the page dictionary that are then encoded. Further, the global dictionary, the page dictionary and the store of unclustered shapes are also encoded.
摘要翻译： 提供了一种利用墨簇的显式表示促进双层图像压缩的系统和方法。 本发明包括分析连接的分量信息的群集形状估计器，提取群集并且将群集存储在全局词典，页面字典或非群集形状的存储中。 来自簇组件的位图估计确定存储在全局字典中的簇的字典位置，然后对其进行编码。 集群位置估计器确定然后被编码的全局字典和/或页字典的集群的页面位置。 此外，还编码了全局字典，页字典和未分簇形状的存储。
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公开(公告)号：US07164797B2
公开(公告)日：2007-01-16
申请号：US10133558
申请日：2002-04-25
IPC分类号： G06K9/68
CPC分类号： G06K9/00442 , G06K9/46 , G06K9/6202 , G06K2209/01
摘要： Systems and methods for performing clustering of a document image are disclosed. A property of an extracted mark from a document is compared to the properties of the existing clusters. If the property of the mark fails to match any of the properties of the existing clusters, the mark is added as a new cluster to the existing cluster. One property that can be utilized is x size and y size, which is the width and height, of the existing clusters. Another property that can be employed is ink size, which refers to the ratio of black pixels to total pixels in a cluster. Yet another property that can be utilized is a reduced mark or image, which is a pixel size reduced version the bitmap of the mark and/or cluster. The above properties can be employed to identify mismatches and reduce the number of bit by bit comparisons performed.
摘要翻译： 公开了用于执行文档图像的聚类的系统和方法。 将来自文档的提取标记的属性与现有集群的属性进行比较。 如果标记的属性无法匹配现有集群的任何属性，则该标记作为新集群添加到现有集群。 可以使用的一个属性是x size和y size，这是现有集群的宽度和高度。 可以使用的另一个属性是墨水大小，其指的是群集中黑色像素与总像素的比例。 可以使用的另一个属性是缩小的标记或图像，其是像素尺寸缩小版本的标记和/或集群的位图。 可以采用上述特性来识别不匹配并减少进行的逐比较比较。
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公开(公告)号：US07024039B2
公开(公告)日：2006-04-04
申请号：US10180649
申请日：2002-06-26
IPC分类号： G06K9/46
摘要： A system and method facilitating image retouching is provided. The invention includes an image retoucher having a boundary detector and an image extender. The invention provides for the image retoucher to extend care pixels of at least one of a foreground and a background near a detected spurious boundary by altering the binary mask used for compression of the foreground and/or the background.
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公开(公告)号：US07016529B2
公开(公告)日：2006-03-21
申请号：US10099388
申请日：2002-03-15
CPC分类号： G06K9/4628 , G06K9/00422 , G06K2209/011
摘要： A system and method facilitating pattern recognition is provided. The invention includes a pattern recognition system having a convolutional neural network employing feature extraction layer(s) and classifier layer(s). The feature extraction layer(s) comprises convolutional layers and the classifier layer(s) comprises fully connected layers. The pattern recognition system can be trained utilizing a calculated cross entropy error. The calculated cross entropy error is utilized to update trainable parameters of the pattern recognition system.
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68.发明授权System and method providing improved data compression via wavelet coefficient encoding 有权系统和方法通过小波系数编码提供改进的数据压缩公开(公告)号：US06891974B1
公开(公告)日：2005-05-10
申请号：US09756348
申请日：2001-01-08
CPC分类号： H04N19/1883 , H04N19/129 , H04N19/63
摘要： A data compression system is provided in accordance with the present invention. The system includes a scanning component which scans at least a portion of a transformed image. The scan is performed substantially in a horizontal direction on a first section of the portion and in a vertical direction on a second section of the portion to enable improved data compression of the transformed image. The horizontal and vertical scan directions are performed via a contiguous scan of the respective sections to further enable improved data compression of the transformed image.
摘要翻译： 根据本发明提供数据压缩系统。 该系统包括扫描变换图像的至少一部分的扫描部件。 基本上在该部分的第一部分上的水平方向上执行扫描，并且在该部分的第二部分上沿垂直方向执行扫描，以改进变换图像的数据压缩。 通过相应部分的连续扫描来执行水平和垂直扫描方向，以进一步实现改进的变换图像的数据压缩。
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