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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Hu, Xuelong Yang, Li Zhang, Gensheng School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. for Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. for Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

This paper addresses an effective issue of content-based image retrieval (CBIR) by presenting Fuzzy Hamming Distance (FHD). Firstly, the theory of FHD is introduced, which includes degree of difference and cardinality of the fuzzy set, and then follows defuzzification of FHD which is used as a fuzzy similarity measure. In the experiment, the image retrieval results show this method can be employed to capture implicitly some semantic contents of the image in addition to other features such as color, texture and shape. Finally, an implemented prototype system demonstrates a promising retrieval performance for a test database, as compared with FUZZYCLUB system. © 2007 IEEE.

关键词： Hamming distance

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A new method for semi-automatic image annotation

A new method for semi-automatic image annotation

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Xuelong, Hu Yuhui, Zhang Li, Yang School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. of Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. of Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

Semantic-based image retrieval bridges the gap between visual features and human understanding of image in the field of image retrieval. Image annotation is one important technology of image retrieval based on the semantic. This paper proposed one method to realize semi-automatic image annotation with the tool Support Vector Machine (SVM). The image collection was divided into two parts, one for manual annotation and the other for testing. After being classified by SVM, the output was changed into a probability, and K-NN algorithm was applied to get the keywords for unlab.led images. The experiments show that the approach is feasible. © 2007 IEEE.

关键词： Support vector machines

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Dependency tree-based anaphoricity determination for coreference resolution

Dependency tree-based anaphoricity determination for corefer...

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International Conference on Asian Language processing

作者： Kong, Fang Zhou, Jianmei Zhou, Guodong Zhu, Qiaoming JiangSu Provincial Key Lab. for Computer Information Processing Technology China School of Computer Science and Technology Soochow University Suzhou China Computer Science and Technology School NanTong University NanTong China

ISBN: (纸本)9780769542881

This paper proposes a new scheme to determine the tree span structure for tree kernel-based anaphoricity determination in coreference resolution. Given a sentence and current mention, it gets all the dependencies, encodes the order of all the words, constructs the corresponding dependency tree and keeps the nodes and the paths related with current mention based on constituent dependencies, while removing the noisy information, eventually leading to a dynamical dependency tree (DDT). Evaluation on the ACE 2003 corpus shows that the DDT is effective for anaphoricity determination, and that applying our anaphoricity determination module in coreference resolution achieves the improv.ment of performance. © 2010 IEEE.

关键词： Anaphoricity determination Coreference resolution Dependency tree Coreference Resolution DDT DEPENDENCE

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A Sentiment Classification Model Based on Syntactic Graph Attention Networks 24

A Sentiment Classification Model Based on Syntactic Graph At...

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2024 International Conference on Intelligent Education and computer technology, IECT 2024

作者： Cheng, Yan Zhou, Ziwei School of Computer Information Engineering Jiangxi Normal University Jiangxi Nanchang330022 China Prov. Key Lab. of Intelligent Information Processing and Affective Computing of Jiangxi Province 330022 China School of Software Jiangxi Normal University 330022 China

ISBN: (纸本)9798400709920

Text Sentiment Classification, a significant task in Natural Language processing, aims to comprehend user needs and expectations by categorizing the sentiments of texts posted on platforms. Despite their utility, existing models for this task do not fully account for the influence of contextual and syntactic text features on sentiment classification. To address these issues, a text sentiment classification model based on syntactic graph attention network is proposed in this study. The model begins by extracting the contextual features of a sentence using BiGRU. It then generates a syntactic graph through a syntactic analyzer, using the contextual features as the node features of the syntactic graph. A syntactic graph attention network is constructed to extract the syntactic features of the syntactic graph. These feature vectors are then input into a softmax function to achieve text sentiment classification. Experimental results indicate that the proposed model outperforms similar models on two public datasets in terms of classification accuracy, thus demonstrating its effectiveness. © 2024 ACM.

关键词： Syntactics

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An access control model in lager-scale P2P file sharing systems

An access control model in lager-scale P2P file sharing syst...

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7th International Conference on Computational Science (ICCS 2007)

作者： Yue Guang-xue Yu Fei Chen Li-ping Chen Yi-jun College of Information Engineering Jiaxing University 314000 China Department of Computer Science and Technology Huaihua University 418000 China State Key Lab. for Novel Software Technology Nanjing University 210093 China Jiangsu Provincial Key Laboratory of Computer Information Processing Technology Suzhou University 2150063 China

ISBN: (纸本)9783540725893

In lager-scale P2P file sharing systems, peers often must interact with unknown or unfamiliar peers without the benefit of trusted third parties or authorities to mediate the interactions. The decentralized and anonymous characteristics of P2P environments make the task of controlling access to sharing information more difficult. In this paper, we identify access control requirements and propose a trust based access control framework for P2P file-sharing systems. The model integrates aspects of trust and recommendation, fairness based participation schemes and access control schemes.

关键词： Distributed computer systems

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Bilinear grid search strategy based support vector machines learning method

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Informatica (Slovenia) 2014年第1期38卷 51-58页

作者： Li, Lin Zhang, Xiaolong Zhang, Kai Liu, Jun School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Prov. Key Lab. of Intelligent Information Processing and Real-time Industrial System China

Support Vector Machines (SVM) learning can be used to construct classification models of high accuracy. However, the performance of SVM learning should be improv.d. This paper proposes a bilinear grid search method to achieve higher computation efficiency in choosing kernel parameters (C, γ) of SVM with RBF kernel. Experiments show that the proposed method retains the advantages of a small number of training SVMs of bilinear search and the high prediction accuracy of grid search. It has been prov.d that bilinear grid search method (BGSM) is an effective way to train SVM with RBF kernel. With the application of BGSM, the protein secondary structure prediction can obtain a better learning accuracy compared with other related algorithms.

关键词： Support vector machines

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Improv.ng nominal SRL in Chinese language with verbal SRL information and automatic predicate recognition

Improving nominal SRL in Chinese language with verbal SRL in...

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2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Li, Junhui Zhou, Guodong Zhao, Hai Zhu, Qiaoming Qian, Peide Jiangsu Provincial Key Lab. for Computer Information Processing Technologies School of Computer Science and Technology Soochow University Suzhou 215006 China Department of Chinese Translation and Linguistics City University of HongKong Hong Kong

This paper explores Chinese semantic role lab.ling (SRL) for nominal predicates. Besides those widely used features in verbal SRL, various nominal SRL-specific features are first included. Then, we improv. the performance of nominal SRL by integrating useful features derived from a state-of-the-art verbal SRL system. Finally, we address the issue of automatic predicate recognition, which is essential for a nominal SRL system. Evaluation on Chinese NomBank shows that our research in integrating various features derived from verbal SRL significantly improv.s the performance. It also shows that our nominal SRL system much outperforms the state-of-the-art ones. © 2009 ACL and AFNLP.

关键词： Natural language processing systems

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Invulnerability optimization analysis of interdependent networks

Invulnerability optimization analysis of interdependent netw...

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2021 IEEE International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Tang, Chunyang Xiao, Yuzhi Zhao, Haixing Ye, Zhonglin College of Computer Qinghai Normal University The Prov. and Ministerial Jt. Constr. of the State Key Lab. of Tibetan Intelligent Info. Proc. and Applic. Key Laboratory of Tibetan Information Processing Min. of Educ. Tibetan Info. Processing and Machine Translation Key Laboratory of Qinghai Province Xining China

ISBN: (纸本)9781665412629

The nodes in interdependent network have both information exchange and information dissemination, and the node degree correlation of network is easier to divide into different community structures. In order to study invulnerability of such networks, the global topology and the local community properties of network are considered in this paper, and attack strategies are proposed based on node overlapping degree and community structure. The relative size s of the most connected sub-graph and global efficiency E of the network are taken as invulnerability measures. Firstly, two kinds of interdependent network models are constructed by using correlation of nodes in different levels (random correlation and preferential correlation), and their static topological indexes are analyzed. Secondly, invulnerability experiments are carried with two kinds of synthetic networks in different attack strategies. Finally, as the application of model, the 'aviation-information' empirical network is constructed, and the influence of information network topology on the aviation network is explored. Combined with numerical simulation, attack strategy based on community structure is the most effective. The network generated by random correlation mechanism between layers has better invulnerability. Small-world information network has little influence on the invulnerability of aviation information network. The results of this paper have a certain guiding significance for model construction mechanism of the invulnerability of interdependent networks. © 2021 IEEE.

关键词： information dissemination

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The Applications of Generalized Computing In Knowledge Management

The Applications of Generalized Computing In Knowledge Manag...

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2005年公共管理国际会议

作者： YAO Min SHEN Bin ZHANG Yan-gu College of Computer Zhejiang University Provincial Key Lab. for Computer Information processing Technology in Jiangsu Suzhou University School of Computer Wenzhou Normal College

Generalized computing is a new kind of intelligent computing systems, which combines symbolic intelligence and computational intelligence (including neural computing, fuzzy computing and evolutional computing) together. By introducing generalized computing into knowledge management, this paper presents a kind of knowledge decision-making model, and a kind of control model of enterprise knowledge flow.

关键词： Generalized computing, Knowledge management, Enterprise management

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Data-consistent Unsupervised Diffusion Model for Metal Artifact Reduction

Data-consistent Unsupervised Diffusion Model for Metal Artif...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Tong, Zhan Wu, Zhan Yang, Yang Mao, Weilong Wang, Shijie Li, Yinsheng Chen, Yang Southeast University Laboratory of Image Science and Technology Nanjing210096 China Southeast University Ministry of Education Key Laboratory of Computer Network and Information Integration Nanjing210096 China Chinese Academy of Sciences Research Center for Medical Artificial Intelligence Shenzhen Institutes of Advanced Technology Shenzhen518055 China School of Computer Science and Engineering Key Lab. of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Laboratory of Image Science and Technology Nanjing210096 China

ISBN: (纸本)9798350337488

Computed Tomography (CT) is an imaging technique widely used in clinical diagnosis. However, high-attenuation metallic implants result in the obstruction of low-energy Xrays and further lead to metal artifacts in the reconstructed CT images. Deep supervised model-based metal artifact reduction(MAR) approaches are limited in clinical applications due to the difficulty in obtaining paired artifact-affected and artifactfree data. Furthermore, these model-based methods lack the consideration of data consistency in the sinogram-domain to perform exact metal trace inpainting. To address these challenges, we propose a Data-consistent unsupErVised diffusiOn model for meTal artifact rEDuction, called DEVOTED-Net. First, DEVOTED-Net leverages prior knowledge to guide the conditional diffusion model for fine-grained metal trace inpainting. Second, an unsupervised MAR framework is designed in the reverse process for the unknown metal traces restoration in the sinogram domain. Third, to further enhance the sinogram-domain data consistency, physics-based consistency constraint loss including conjugateray consistency loss and accumulation-ray consistency loss is designed. Extensive experiments are carried out to verify the performance of our algorithm on the publicly availab.e dataset and clinical experimental dataset. This efficient, accurate, and reliable MAR approach holds great potential in clinics. © 2023 IEEE.

关键词： computed tomography deep unsupervised learning denoising diffusion probabilistic model Metal artifact reduction physics-based consistency constraint

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