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检索条件"机构=The Key Laboratory of Intelligent Computing and Signal Processing"
3652 条 记 录,以下是3601-3610 订阅
排序:
A logical foundation for ontology representation in NKI
A logical foundation for ontology representation in NKI
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IEEE International Conference on Natural Language processing and Knowledge Engineering (NLP-KE)
作者: Yu Sun Yuefei Sui Institute of Computer Science and Information Technology Yunnan Normal University Kunming China Graduate School Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China
A formal representation of ontologies is proposed, based on F-logic and O-logic; and the works in the building of ontologies in NKI. An ontology includes class frames, slot frames, class-slot frames, object frames and... 详细信息
来源: 评论
Knowledge Energy in Knowledge Flow Networks
Knowledge Energy in Knowledge Flow Networks
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International Conference on Semantics, Knowledge and Grid (SKG)
作者: Hai Zhuge Weiyu Guo Xiang Li Lianhong Ding China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate School of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN
A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the ... 详细信息
来源: 评论
A novel feature extraction algorithm
A novel feature extraction algorithm
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International Conference on Machine Learning and Cybernetics (ICMLC)
作者: Shi-Fei Ding Zhong-Zhi Shi Vun-Cheng Wang Shu-Shan Li College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China
Feature extraction or selection is one of the most important steps in pattern recognition or pattern classification, data mining, machine learning and so on. In this paper, we introduce the information theory, propose... 详细信息
来源: 评论
Information feature analysis and improved algorithm of PCA
Information feature analysis and improved algorithm of PCA
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International Conference on Machine Learning and Cybernetics (ICMLC)
作者: Shi-Fei Ding Zhong-Zhi Shi Yong Liang Feng-Xiang Jin College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China College of Geo-Information Science and Engineering Shandong University of Science and Technology Qingdao China
Principal component analysis (PCA) is an important method in multivariate statistical analysis, and its main idea is compression of dimensionality including variables and samples. In this paper, based on the ideas con... 详细信息
来源: 评论
Survey of 3D mesh model segmentation and application
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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2005年 第8期17卷 1647-1655页
作者: Sun, Xiaopeng Li, Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100039 China
In this paper, we present a brief summary to 3D mesh model segmentation techniques, including definition, latest achievements, classification and application in this field. Then evaluations on some of typical methods,... 详细信息
来源: 评论
Non-parametric foreground/background segmentation method by fusion of intensity and edge feature
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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2005年 第6期17卷 1278-1284页
作者: Chen, Rui Deng, Yu Xiang, Shiming Li, Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100039 China
This paper presents a novel segmentation method based on a non-parametric background model that has the ability of modeling multi-model. Firstly, both the intensity and edge features are used to improve robustness of ... 详细信息
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Granular theorem of quotient space in image segmentation
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Jisuanji Xuebao/Chinese Journal of Computers 2005年 第10期28卷 1680-1685页
作者: Liu, Ren-Jin Huang, Xian-Wu Department of Computer Science and Technology West Anhui University Lu'an 237012 China Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China School of Electronic and Information Engineering Soochow University Suzhou 215006 China
Based on the quotient space granular theorem, the image segmentation concept is analyzed and the image segmentation methods are studied, and then the quotient space granular theorem of image segmentation is demonstrat... 详细信息
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Modeling the growth of future web
Modeling the growth of future web
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Thirteenth International World Wide Web Conference Proceedings, WWW2004
作者: Zhuge, Hai Chen, Xue Li, Xiang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China
The future Web cart be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth - adding it to the network - to death - removing it from... 详细信息
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An automatic semantic relationships discovery approach
An automatic semantic relationships discovery approach
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Thirteenth International World Wide Web Conference Proceedings, WWW2004
作者: Zhuge, Hai Zheng, Liping Zhang, Nan Li, Xiang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for const... 详细信息
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Sparse bayesian learning based on an efficient subset selection
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International Symposium on Neural Networks, ISNN 2004
作者: Bo, Liefeng Wang, Ling Jiao, Licheng Institute of Intelligent Information Processing and National Key Laboratory for Radar Signal Processing Xidian University Xi’an710071 China
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale problems. Experiments on synthetic and ... 详细信息
来源: 评论