中国科学院机构知识库网格系统: 检索

浏览/检索结果: 共8条，第1-8条

帮助

条数/页：排序方式：
	Modified Matrix Decomposition Method for Generating Multivariate Three-Dimensional Cross-Correlated Random Fields 期刊论文 OAI收割 ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2023 作者: Tian, Ning; Chen, Jian; Wang, Zhansheng; Tian, Kaiwei; Huang, Juehao \| 收藏 \| 浏览/下载：16/0 \| 提交时间：2023/08/02 Soil heterogeneity Spatial variability Modified matrix decomposition Multivariate random field Cross-correlation structure
	Compressive Subspace Learning With Antenna Cross-Correlations for Wideband Spectrum Sensing 期刊论文 OAI收割 IEEE TRANSACTIONS ON COMMUNICATIONS, 2020, 卷号: 68, 期号: 9, 页码: 5406-5419 作者: Gong TR(宫铁瑞); Yang ZJ(杨志家); Zheng M(郑萌); Liu ZF(刘志峰); Wang GS(王庚善) \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2020/10/10 MIMO communication Correlation Sensors Wideband Receiving antennas Spatial diversity Compressive subspace learning wideband spectrum sensing cognitive radio MIMO antenna cross-correlation
	Spatial pyramidal cross correlation for particle image velocimetry 期刊论文 OAI收割 SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2018, 卷号: 61, 期号: 6, 页码: 867-878 作者: Wang HP; Wu P; Gao Q; Wang JJ; Wang JJ 收藏 \| 浏览/下载：27/0 \| 提交时间：2018/07/17 Particle Image Velocimetry (Piv) Cross Correlation Spatial Resolution Moving Average
	A likelihood-based spatial statistical transformation model (LBSSTM) of regional economic development using DMSP/OLS time-series nighttime light imagery 期刊论文 OAI收割 SPATIAL STATISTICS, 2017, 卷号: 21, 页码: 421-439 作者: Li, Chang; Li, Guie \| 收藏 \| 浏览/下载：27/0 \| 提交时间：2019/09/25 DMSP/OLS nighttime light data Likelihood-based spatial statistical transformation model (LBSSTM) Time series analysis Prediction ESDA Spatial cross correlation
	The spatial-temporal evolution of coherent structures in log law region of turbulent boundary layer 期刊论文 OAI收割 Acta Mechanica Sinica, 2015, 卷号: 31, 期号: 1, 页码: 16-24 作者: Zheng XB; Jiang N 收藏 \| 浏览/下载：24/0 \| 提交时间：2015/04/28 Log law region in TBL Spatial-temporal cross-correlation Tomographic TRPIV Coherent structures Low and high speed streaks Multi-resolution wavelet decomposition
	Climate warming increases biodiversity of small rodents by favoring rare or less abundant species in a grassland ecosystem SCI/SSCI论文 OAI收割 2013 Jiang G. S.; Liu J.; Xu L.; Yu G. R.; He H. L.; Zhang Z. B. 收藏 \| 浏览/下载：30/0 \| 提交时间：2014/12/24 climate change cross-correlation function rare species small mammal biodiversity time lag small mammal diversity spatial synchrony inner-mongolia brandts voles richness dynamics patterns desert scale plant
	Mapping soil organic matter using the topographic wetness index: A comparative study based on different flow-direction algorithms and kriging methods SCI/SSCI论文 OAI收割 2010 作者: Yang L.; Pei T. 收藏 \| 浏览/下载：37/0 \| 提交时间：2012/06/08 Collocated cokriging Single-flow-direction (SFD) Multiple-flow-direction (MFD) Auto-correlation Cross-correlation Terrain variable Digital soil mapping spatial interpolation drainage networks northeast china black soil prediction elevation indicators regression topmodel models
	Target track system design based on circular projection (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Song H.-J.; Zhu M.; Hu S.; Shen M.-L. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 Template matching is the process of searching the present and the location of a reference image or an object in a scene image. Template matching is a classical problem in a scene analysis: given a reference image of an object decide whether that object exists in a scene image under analysis and find its location if it does. The template matching process involves cross-correlating the template with the scene image and computing a measure of similarity between them to determine the displacement. The conventional matching method used the spatial cross-correlation process which is computationally expensive. Some algorithms are proposed for this speed problem such as pyramid algorithm but it still can't reach the real-time for bigger model image. Moreover the cross-correlation algorithm can't be effective when the object in the image is rotated. Therefore the conventional algorithms can't be used for practical purpose. In this paper an algorithm for a rotation invariant template matching method based on different value circular projection target tracking algorithm is proposed. This algorithm projects the model image as circular and gets the radius and the sum of the same radius pixel value. The sum of the same radius pixel value is invariable for the same image and the any rotated angle image. Therefore this algorithm has the rotation invariant property. In order to improve the matching speed and get the illumination invariance the different value method is combined with circular projection algorithm. This method computes the different value between model image radius pixel sum and the scene image radius pixel sum so that it gets the matching result. The pyramid algorithm also is been applied in order to improve the matching speed. The high speed hardware system also is been design in order to meet the real time requirement of target tracking system. The results show that this system has the good rotate invariance and real-time property.