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    • 1. 发明申请
    • CONTROLLING DATA READING MODE OF MEMORY
    • 控制存储器的数据读取模式
    • US20130124879A1
    • 2013-05-16
    • US13398731
    • 2012-02-16
    • Yong ZhangYuan LiZhi JiangXiaofei LiJian Sun
    • Yong ZhangYuan LiZhi JiangXiaofei LiJian Sun
    • G06F1/30
    • G06F13/385
    • An embodiment of the invention includes a device for controlling data reading mode of a hard disk host apparatus. The device comprises a power converter circuit, a power supply toggle-switching circuit, a hard disk access port selection module, a hard disk host converter module, and a power control module. The power control module judges whether the motherboard supplies power for the apparatus in order to select the power supply mode and data transmission channel for the hard disk. If the motherboard supplies power, then power is supplied to the hard disk via the motherboard and the hard disk host controller is selected to provide the data transmission channel for the hard disk. If the motherboard supplies no power, then power is supplied to the hard disk via the external device receptacle and the hard disk host converter module is selected to provide the data transmission channel for the hard disk.
    • 本发明的实施例包括用于控制硬盘主机装置的数据读取模式的装置。 该装置包括电源转换器电路,电源开关切换电路,硬盘访问端口选择模块,硬盘主机转换器模块和电源控制模块。 电源控制模块判断主板是否为设备供电,以便选择硬盘的电源模式和数据传输通道。 如果主板供电,则通过主板向硬盘供电,并选择硬盘主机控制器为硬盘提供数据传输通道。 如果主板没有电源,则通过外部设备插座向硬盘供电,并选择硬盘主机转换器模块为硬盘提供数据传输通道。
    • 5. 发明授权
    • Visual-cue refinement of user query results
    • 用户查询结果的视觉提示细化
    • US09355179B2
    • 2016-05-31
    • US12890097
    • 2010-09-24
    • Yu-Ting KuoYi LiFang WenQifa KeJian Sun
    • Yu-Ting KuoYi LiFang WenQifa KeJian Sun
    • G06F17/30
    • G06F17/30867G06F17/30651G06F17/30696
    • Methods and computer-storage media having computer-executable instructions embodied thereon that facilitate refining query results using visual cues are provided. Query results are determined in response to an indication of a user query. One or more groups of query results are generated from the query results based on categories of query results that share similar features. Visual cues are associated with each of the query result groups. Visual cues, in association with query result groups, are presented to a user. Query results associated with a selected visual cue may be presented to a user. A refined user query may be generated based on a selected visual cue.
    • 提供了具有实现在其上的计算机可执行指令的方法和计算机存储介质,其使用视觉提示便于精简查询结果。 响应于用户查询的指示来确定查询结果。 基于共享类似特征的查询结果的类别,从查询结果生成一组或多组查询结果。 视觉线索与每个查询结果组相关联。 与查询结果组相关联的视觉提示被呈现给用户。 与所选择的视觉提示相关联的查询结果可以被呈现给用户。 可以基于所选择的视觉提示来生成精细的用户查询。
    • 7. 发明授权
    • Image super-resolution using gradient profile prior
    • 使用梯度轮廓的图像超分辨率
    • US09064476B2
    • 2015-06-23
    • US12245712
    • 2008-10-04
    • Jian SunHeung-Yeung Shum
    • Jian SunHeung-Yeung Shum
    • G06K9/32G09G5/391G06T3/40
    • G09G5/391G06T3/4053G09G2340/0407
    • Described is a technology by which a low-resolution image is processed into a high-resolution image, including by performing processing in the gradient domain. A gradient profile corresponding to the lower-resolution image is transform into a sharpened image gradient. A high-resolution gradient profile is estimated from a low-resolution gradient profile, e.g., by multiplying the low-resolution gradient profile by a transform ratio that is based upon learned shape parameters, learned sharpness values and a curve distance to an edge pixel along the gradient profile. The transform ratio is used to transform a low-resolution gradient field to a high-resolution gradient field. Reconstructing the higher-resolution image is performed by using the high-resolution gradient field as a gradient domain constraint, e.g., in along with a reconstruction constraint obtained from image domain data. An energy function is minimized by enforcing the gradient domain constraint and the reconstruction constraint, e.g., by performing a gradient descent algorithm.
    • 描述了将低分辨率图像处理成高分辨率图像的技术,包括通过在梯度域中执行处理。 对应于较低分辨率图像的渐变曲线被转换成锐化的图像梯度。 从低分辨率梯度轮廓估计高分辨率梯度轮廓,例如,通过将低分辨率梯度轮廓乘以基于学习的形状参数,学习的锐度值和到边缘像素的曲线距离的变换比, 梯度轮廓。 变换比用于将低分辨率梯度场转换为高分辨率梯度场。 通过使用高分辨率梯度场作为梯度域约束,例如与从图像域数据获得的重建约束一起,进行重建高分辨率图像。 通过执行梯度域约束和重构约束,例如通过执行梯度下降算法来最小化能量函数。