会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 7. 发明授权
    • Test support apparatus
    • 测试支持设备
    • US08870172B2
    • 2014-10-28
    • US13268165
    • 2011-10-07
    • Meng-Bin YuYang ChenWei LiangYu-Lin Liu
    • Meng-Bin YuYang ChenWei LiangYu-Lin Liu
    • B23Q3/02G01M99/00G01M7/02
    • G01M99/00G01M7/027
    • A test support apparatus includes a supporting mechanism supporting a product, a holding post pressed on the product, a positioning assembly, an operating member and a clamping member. The positioning assembly is attached to the supporting mechanism and the holding post. The positioning assembly includes a positioning member and a moving member. The moving member is attached to the holding post, and moveably relative to the positioning member to adjust a distance between the holding post and the supporting mechanism. The operating member is rotatably attached to the positioning member. The clamping member is rotatably attached to the operating member and rotatable relative to the operating member about a first axis. The clamping member engaged with the supporting mechanism, and the operating member is rotatable relative to the positioning member about a second axis to rotate the clamping member about the first axis to disengaged from the supporting mechanism.
    • 测试支撑装置包括支撑产品的支撑机构,压在产品上的保持柱,定位组件,操作构件和夹紧构件。 定位组件附接到支撑机构和保持柱。 定位组件包括定位构件和移动构件。 移动构件附接到保持柱,并且相对于定位构件可移动地调节保持柱和支撑机构之间的距离。 操作构件可旋转地附接到定位构件。 夹紧构件可旋转地附接到操作构件并且可围绕第一轴线相对于操作构件旋转。 夹持构件与支撑机构接合,并且操作构件可相对于定位构件围绕第二轴线旋转,以使夹紧构件围绕第一轴线旋转以与支撑机构分离。
    • 8. 发明授权
    • Enhancing video using super-resolution
    • 使用超分辨率增强视频
    • US08861893B2
    • 2014-10-14
    • US13246253
    • 2011-09-27
    • Yang ChenDavid R. GerweDeying Zhang
    • Yang ChenDavid R. GerweDeying Zhang
    • G06K9/32G06K9/36H04N7/14G06T3/40
    • G06T3/4053G06T2207/10016
    • A method and apparatus for processing images. A portion of a selected image in which a moving object is present is identified. The selected image is one of a sequence of images. Pixels in a region of interest are identified in the selected image. First values are identified for a first portion of the pixels using the images and first transformations. The first portion of the pixels corresponds to the background in the selected image. A first transformation is configured to align features of the background between one image in the images and the selected image. Second values are identified for a second portion of the pixels using the images and second transformations. The second portion of the pixels corresponds to the moving object in the selected image. A second transformation is configured to align features of the moving object between one image in the images and the selected image.
    • 一种用于处理图像的方法和装置。 识别其中存在移动物体的所选图像的一部分。 所选择的图像是图像序列之一。 在所选择的图像中识别感兴趣区域中的像素。 使用图像和第一变换来识别第一部分像素的第一值。 像素的第一部分对应于所选图像中的背景。 第一变换被配置为对准图像中的一个图像与所选图像之间的背景的特征。 使用图像和第二变换来识别第二部分像素的第二值。 像素的第二部分对应于所选图像中的移动物体。 第二变换被配置为使图像中的一个图像与所选择的图像之间的移动物体的特征对准。
    • 9. 发明授权
    • Optimal multi-class classifier threshold-offset estimation with particle swarm optimization for visual object recognition
    • 用于视觉对象识别的粒子群优化的最优多类分类器阈值偏移估计
    • US08768868B1
    • 2014-07-01
    • US13440881
    • 2012-04-05
    • Shinko Y. ChengYang ChenDeepak KhoslaKyungnam Kim
    • Shinko Y. ChengYang ChenDeepak KhoslaKyungnam Kim
    • G06N5/00
    • G06N5/00
    • Described is a system for multi-class classifier threshold-offset estimation for visual object recognition. The system receives an input image with input features for classifying. A pair-wise classifier is trained for each pair of a plurality of object classes. A set of classification responses is generated, and a multi-class receiver-operating-characteristics (ROC) curve is computed for a set of threshold-offsets. An objective function of classification performance is computed from the ROC curve and optimized using particle swarm optimization (PSO) to generate a set of optimized threshold-offsets. The optimized threshold-offsets are then applied to the classification responses. The resulting classification responses are compared to a predetermined value to classify each input feature as belonging to one object class or another. The tuning of the threshold-offsets with (PSO) improves classification performance in a visual object recognition system.
    • 描述了用于视觉对象识别的多类分类器阈值偏移估计的系统。 系统接收具有输入特征进行分类的输入图像。 针对多对象类的每一对训练一对成对的分类器。 生成一组分类响应,并计算一组阈值偏移量的多类接收器操作特性(ROC)曲线。 从ROC曲线计算分类性能的目标函数,并使用粒子群优化(PSO)进行优化,以生成一组优化的阈值偏移。 然后将优化的阈值偏移应用于分类响应。 将所得分类响应与预定值进行比较,以将每个输入特征分类为属于一个对象类或另一对象类。 使用(PSO)调整阈值偏移可提高视觉对象识别系统中的分类性能。