中国科学院机构知识库网格系统: 检索

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	XLORE2: Large-Scale Cross-Lingual Knowledge Graph Construction and Application 期刊论文 OAI收割 Data Intelligence, 2019, 卷号: 1, 期号: 1, 页码: 77-98 作者: Hailong Jin; Chengjiang Li; Jing Zhang; Lei Hou; Juanzi Li \| 收藏 \| 浏览/下载：18/0 \| 提交时间：2021/04/30 Knowledge Base Completion Knowledge Linking Property Matching Taxonomy Alignment Type Inference Entity Linking
	Gradient characteristics and strength matching in friction stir welded joints of Fe-18Cr-16Mn-2Mo-0.85N austenitic stainless steel 期刊论文 OAI收割 Materials Science and Engineering a-Structural Materials Properties Microstructure and Processing, 2014, 卷号: 616, 页码: 246-251 D. X. Du; R. D. Fu; Y. J. Li; L. Jing; Y. B. Ren; K. Yang 收藏 \| 浏览/下载：39/0 \| 提交时间：2015/01/14 High-nitrogen steel Friction stir welding Microstructure gradient Mechanical property Strength matching hall-petch relationship nitrogen
	Digital image information encryption based on Compressive Sensing and double random-phase encoding technique 期刊论文 OAI收割 OPTIK, 2013, 卷号: 124, 期号: 16, 页码: 2514-2518 作者: Lu, Pei; Xu, Zhiyong; Lu, Xi; Liu, Xiaoyong 收藏 \| 浏览/下载：26/0 \| 提交时间：2015/04/17 Compressive Sensing (CS) Double random-phase encoding (DRPE) Orthogonal Matching Pursuit (OMP) Restricted Isometry Property (RIP)
	Fast covariance matching based on Genetic Algorithm (EI CONFERENCE) 会议论文 OAI收割 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2010, September 23, 2010 - September 25, 2010, Chengdu, China 作者: Zhang X.; Zhang L.; Zhang L.; Zhang X.; Zhang X. 收藏 \| 浏览/下载：13/0 \| 提交时间：2013/03/25 This paper proposes an effective framework to boost the efficiency of covariance matching. In this framework covariance matrices are used to match object in complex environment by fusing multiple features. Then Genetic Algorithm (GA) is employed to improve the processing speed of covariance matching. To take advantage of the property of GA for the optimization in large search spaces to covariance matching a fitness function is designed using the distances between the covariance matrices of model and candidate regions. Experimental results show that the proposed approach can improve the processing speed of covariance matching observably. The computing speed of the proposed method is at least 7 times than that of exhaustive searching. 2010 IEEE.
	tree-based service discovery in mobile ad hoc networks 会议论文 OAI收割 2010 IEEE Asia-Pacific Services Computing Conference, APSCC 2010, Hangzhou, 40883 Liao Mingxue; He Jing; Zhu Rongfu; Wang Xianqing; He Xiaoxin \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2011/03/31 communication capability information sharing local service repository mobile ad hoc networks property-changing services seamless collaborations service capability service matching process service oriented architectures service quality target service tree-based service discovery mechanism typical mobile networks wireless communication overheads Web services groupware radiocommunication service-oriented architecture telecommunication computing trees (mathematics)
	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 novel starting-point-independent wavelet coefficient shape matching (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Hu S.; Zhu M.; Wu C.; Song H.-J. 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/03/25 In many computer vision tasks in order to improve the accuracy and robustness to the noise wavelet analysis is preferred for the natural multi-resolution property. However the wavelet representation suffers from the dependency of the starting point of the sampled contour. For overcoming the problem that the wavelet representation depends on the starting point of the sampled contour the Zernike moments are introduced and a novel Starting-Point-lndependent wavelet coefficient shape matching algorithm is presented. The proposed matching algorithm firstly gains the object contours and give the translation and scale invariant object shape representation. The object shape representation is converted to the dyadic wavelet representation by the wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments consider the Zernike moments as the feature vector to calculate the dissimilarity between the object and template image which overcoming the problem of dependency of starting point. The experimental results have proved the proposed algorithm to be efficient precise and robust.