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    • 32. 发明申请
    • CHANGE DETECTION AND CHANGE MONITORING OF NATURAL AND MAN-MADE FEATURES IN MULTISPECTRAL AND HYPERSPECTRAL SATELLITE IMAGERY
    • 更多检测和更改监视和多维度卫星图像中自然和人为特征的监测
    • US20160307073A1
    • 2016-10-20
    • US15133387
    • 2016-04-20
    • Los Alamos National Security, LLC
    • Daniela Irina Moody
    • G06K9/66G06K9/00G06K9/62
    • G06K9/0063G06K9/00536G06K9/6218
    • An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.
    • 土地覆被分类,季节性和年度变化检测和监测方法以及人为特征变化的识别可能会使用稀疏近似聚类(CoSA)对学习词典中的稀疏表示进行聚类。 Hebbian学习规则可用于构建适用于区域卫星图像数据的多光谱或高光谱多分辨率字典。 可以使用学习词典上的像素补丁的稀疏图像表示来执行无监督的k均值聚类到土地覆盖类别。 聚类过程在检测实际变异性方面表现为分类器。 这种方法可以结合光谱和空间纹理特征来检测地质,植被,水文和人为特征,以及这些特征随时间的变化。
    • 36. 发明授权
    • Apparatus and method for noninvasive particle detection using doppler spectroscopy
    • 使用多普勒光谱法进行非侵入性粒子检测的装置和方法
    • US09354094B2
    • 2016-05-31
    • US13225750
    • 2011-09-06
    • Dipen N. Sinha
    • Dipen N. Sinha
    • G01F1/74G01F1/66G01F1/704
    • G01F1/663G01F1/704G01F1/74G01N15/02G01N29/036G01N2015/0053G01N2291/017G01N2291/02416
    • An apparatus and method for noninvasively detecting the presence of solid particulate matter suspended in a fluid flowing through a pipe or an oil and gas wellbore are described. Fluid flowing through a conduit containing the particulate solids is exposed to a fixed frequency (>1 MHz) of ultrasonic vibrations from a transducer attached to the outside of the pipe. The returning Doppler frequency shifted signal derived from the scattering of sound from the moving solid particles is detected by an adjacent transducer. The transmitted signal and the Doppler signal are combined to provide sensitive particulate detection. The magnitude of the signal and the Doppler frequency shift are used to determine the particle size distribution and the velocity of the particles. Measurement of the phase shift between the applied frequency and the detected Doppler shifted may be used to determine the direction of motion of the particles.
    • 描述了用于非侵入性地检测悬浮在流过管道或油气井的流体中的固体颗粒物质的存在的装置和方法。 流过包含颗粒固体的管道的流体暴露于来自连接到管外部的传感器的超声振动的固定频率(> 1MHz)。 通过相邻的换能器检测来自移动固体颗粒的声音散射得到的返回多普勒频移信号。 发射信号和多普勒信号被组合以提供敏感的微粒检测。 信号的大小和多普勒频移用于确定粒子的粒度分布和粒子的速度。 所施加的频率和检测到的多普勒频移之间的相移的测量可以用于确定颗粒的运动方向。