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	A Quantum-Inspired Similarity Measure for the Analysis of Complete Weighted Graphs 期刊论文 OAI收割 IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 3, 页码: 1264-1277 作者: Bai, Lu; Rossi, Luca; Cui, Lixin; Cheng, Jian; Hancock, Edwin R. \| 收藏 \| 浏览/下载：48/0 \| 提交时间：2020/03/30 Kernel Quantum computing Weight measurement Image edge detection Time series analysis Entropy Laplace equations Financial networks graph kernels graph similarity Jensen-Shannon divergence quantum walks
	基于直方图处理和新型相似性度量函数的小尺寸目标跟踪算法期刊论文 OAI收割信号处理, 2010, 卷号: 26, 期号: 6, 页码: 891-897 陈建军; 安国成; 张索非; 吴镇扬收藏 \| 浏览/下载：16/0 \| 提交时间：2011/05/23 小尺寸目标跟踪均值移动直方图处理相似性度量权值计算Small target tracking Mean shift Histogram processing Similarity measure Weight computing
	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.
	A question answering system on special domain and the implementation of speech interface 期刊论文 OAI收割 COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, 2006, 卷号: 3878, 页码: 458-469 作者: Hu, HQ; Ren, FJ; Kuroiwa, S; Zhang, SW; Gelbukh, A 收藏 \| 浏览/下载：14/0 \| 提交时间：2015/11/08 question answering system similarity computing special domain FSN speech recognition Chinese