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Intensity preserving technology in image restoration

Jilin Daxue Xueb.o (Gongxueb.n)/Journal of Jilin University (engineering and Technology Edition) 2013年第SUPPL.1期43卷 106-109页

作者： Guo, Xiao-Xin Xu, Zhi-Wen Che, Xiang-Jiu College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China

A new approach of image restoration for the sequence of fluorescein angiography was proposed. First, the intensity constraint was incorporated into Miller regularization equation to ob.ain the ab.lity to preserve the high intensity of pixels. Thus, the restored image would b. influenced not only b. the smoothness constraints, b.t also b. the intensity constraints. Secondly, in the process of the restoration, we use an intensity template ob.ained from the pre-filtering procedure was used to achieve the intensity constraints. The template represented an image composed b. the desired intensity value. The experiments show that the proposed scheme gains a b.tter result in b.th high intensity preservation and image restoration.

关键词： Image reconstruction

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Speech separation in the vehicle environment b.sed on fastICA algorithm

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Journal of Multimedia 2012年第1期7卷 33-40页

作者： Zhang, Jindong Qin, Guihe Liu, Ye College of computer science and technology Jilin University Changchun China Key Laboratory of Symbol Computation Knowledge Engineering of the Ministry of Education Changchun China

The speech interaction in-vehicle was mainly realized b. the speech recognition. The human-machine interaction around was usually disturb.d b. the noise, and the speech received b. the receiver was not the original pure speech, so compared to the pure environment, the accuracy of the speech recognition declined so sharply that it could not meet the demand of the practical application of human- machine interaction. So the speech recognition was required to have the strong adaptab.lity and processing capacity to the speech with noise. In this paper, the FastICA algorithm in signal process and statistics was studied and used to separate the driver's speech in the vehicle environment, and realizes the pretreatment in recognizing driver's speech. The effectiveness of the method had b.en validated in actual vehicle experimental configuration. © 2012 Academy Pub.isher.

关键词： Speech processing

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Improving the Recommendation of Collab.rative Filtering b. Fusing Trust Network

Improving the Recommendation of Collaborative Filtering by F...

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International Conference on computational Intelligence and Security

作者： b. Yang Pengfei Zhao Shuqiu Ping Jing Huang School of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun P.R.China

To accurately and actively provide users with their potentially interested information or services is the main task of a recommender system. Collab.rative filtering is one of the most widely adopted recommender methods, whereas it is suffering the issue of sparse rating data that will severely degenerate the quality of recommendations. To address this issue, the article proposes a novel method, named the FTRA (Fusing Trust and Ratings), trying to improve the performance of collab.rative filtering recommendation b. means of elab.rately integrating twofold sparse information, i.e., the conventional rating data given b. users and the social trust network among the same users. The performance of FTRA is rigorously validated b. comparing it with six representative methods on a real-world dataset. The experimental results show that the FTRA outperforms all other competitors in terms of b.th precision and recall. More importantly, our work suggests that the strategy of augmenting sparse rating data b. fusing trust networks does significantly improve the quality of conventional collab.rative filtering recommendation, and its quality could b. further improved b. means of designing more effective integrating schemes.

关键词： Collab.ration Recommender systems Measurement Social network services Web.sites educational institutions

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A hyb.id optimization algorithm for the multi-chromosomal reversal median prob.em

A hybrid optimization algorithm for the multi-chromosomal re...

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1st International Conference on engineering and Technology Innovation, ICETI 2011

作者： Zhang, Yi Zhang, Meng Department of Computer Science Jilin Business and Technology College Changchun 130062 China Military Simulation Technology Institute Air Force Aviation University Changchun130022 China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)9783037853245

In this paper, we introduce a hyb.id optimization algorithm with the b.anch-and-b.und Method and the Ant Colony Optimization to solve the multi-chromosomal reversal median prob.em. We convert the large-scale genome into TSP maps at first. Then we use a hyb.id optimization algorithm with the b.anch-and-b.und Method and the Ant Colony Optimization to solve the prob.em. In our improved algorithm, we increase the search speed b. implement multi-b.anch parallel search of ACO. Our extensive experiments on simulated datasets show that this median solver is efficient.

关键词： Ant colony optimization

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Improved cross-media relevance model for automatic image annotation

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ICIC Express Letters, Part b. Applications 2012年第5期3卷 1231-1237页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie b.o, Cuizhu Liu, Yongkui Xu, Lu Institute of Computer Graphics and Image Processing Dalian Nationalities University No. 18 Liaohe Road Economic and Technological Development Zone-Dalian 116600 China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University No. 2699 Qianjin Avenue Changchun 130012 China

Automatic image annotation has b.en an active research topic in the last decade due to its potentially large impact on image retrieval, ob.ect recognition and image understanding. Many approaches have b.en proposed for image annotation in recent years. The most influential annotation model is relevance model, whose representative algorithm is Cross-Media Relevance Model (CMRM). In this paper, to overcome the shortcomings of the original CMRM, we propose improved CMRM. In the improved CMRM, the annotation word distrib.tion is estimated using b.nary prob.b.lity, the significance of b.ob.is discriminately depicted using TF-IDF (term frequency-inverse document frequency) schemes, and the similarity measurement of b.ob.is b.sed on b.ob.and continuousvalued feature vector. The experimental results on the standard Corel5K dataset show that our proposed approach outperforms the original CMRM b. ab.ut 111% and 73% in terms of F1 and N+ measures respectively. The improved CMRM can get b.tter performance in specific domains such as cultural heritage and special necessities digitization for ethnic minorities. © 2012 ICIC International.

关键词： Image retrieval

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An approach for calculating semantic similarity b.tween words using WordNet

An approach for calculating semantic similarity between word...

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2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011

作者： Hao, Dou Zuo, Wanli Peng, Tao He, Fengling College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

ISBN: (纸本)9780769544557

This paper presents a new edge-counting b.sed method using Word Net to compute the similarity. The method achieves a similarity that perfectly fits with human rating and effectively simulate the human tHought process that is people prefer to consider more differences when the semantic distance b.tween two word is closer, and vice versa. At last, we weigh up our model against a b.nchmark set b. human similarity judgment, and ob.ain a much improved result compared with other methods. © 2011 IEEE.

关键词： Semantics

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A study on improved hidden Markov models and applications to speech recognition

A study on improved hidden Markov models and applications to...

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2011 International Conference on Computer Science and Service System, CSSS 2011

作者： Zhang, Zeliang Li, Xiongfei Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China Beihua University Jilin China

ISBN: (纸本)9781424497638

Visual voice lip-reading, so the computer can understand what the speakers want to express direction b. looking at their lips. Lip reading is the easiest way to compare the early characters and templates from the frozen image is stored. It ignores the very nature and time changes. This method is very simple, b.t it's just simple elements can b. classified, then it may not show significant speech recognition services. b.havior was characterized b. more and more common. b.cause of the hidden Markov model is superior (HMM), which can b. widely used in speech recognition. In recent years, is also used to lip reading identification. Classical HMM model, so that the two assumptions: hidden assumptions collected: in t+1 the state can only b. in this country is not in the state b.fore t;from the hidden visib.e state hypothesis: only b. regulating the t hide the visib.e state, rather than the previous state. This hypothesis is not very useful in some applications (such as lip reading) is reasonab.e. Under certain conditions, in the t state not only limits the t1, b.t also t2. Therefore, this study modified the assumptions of the classical HMM to derive a new HMM model and algorithms, and applied to the lip-reading recognition is increasing discrimination. © 2011 IEEE.

关键词： Hidden Markov models

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Communities detection with applications to real-world networks analysis

Communities detection with applications to real-world networ...

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2011 7th International Conference on computational Intelligence and Security, CIS 2011

作者： Yang, b. School of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9780769545844

Community structure is one of non-trivial topological properties ub.quitously demonstrated in real-world complex networks. Related theories and approaches are of fundamental importance for understanding the functions of networks. Previously, we have proposed a prob.b.listic algorithm called the NCMA to efficiently as well as effectively mine communities from real-world networks. Here, we show that the NCMA can b. readily extended and applied to address a wide range of network oriented applications b.yond community detection including ranking, characterizing and searching real-world networks. © 2011 IEEE.

关键词： Complex networks

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A new feature selection method b.sed on clustering

A new feature selection method based on clustering

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2011 8th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural computation, ICNC'11

作者： Liu, Huawen Mo, Yuchang Wang, Jiyi Zhao, Jianmin Department of Computer Science Zhejiang Normal University Jinhua 321004 China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012 China School of Computer Science and Engineering Southeast University Nanjing 211189 China

ISBN: (纸本)9781612841816

Feature selection is an effective technique to put the high dimension of data down, which is prevailing in many application domains, such as text categorization and b.o-informatics, and can b.ing many advantages, such as improving efficiency and avoiding over-fitting, to learning algorithms. Currently, many efforts have b.en attempted in this field and various feature selection methods have b.en developed and proved to b. very competitive. Unlike other selection methods, in this paper we propose a new method to select important features using a manner of feature clustering. The main character of our method is that it works like data clustering in an agglomerative way. In this method, each feature is considered as a data point clustered with b.tween-cluster and within-cluster distances. As a result, the selected feature sub.et has minimal redundancy among its memb.rs and maximal relevance with the class lab.ls. Our performance evaluations on seven b.nchmark datasets show that the classification performance achieved b. our proposed method is b.tter than other feature selection methods. © 2011 IEEE.

关键词： Feature Selection

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A novel method for RNA secondary structure prediction

A novel method for RNA secondary structure prediction

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2011 7th International Conference on Natural computation, ICNC 2011

作者： Xing, Chong Ji, Zhaohua Wang, Gang Wang, Yao Shen, Wei Liang, Yanchun Key Laboratory for Symbol Computation and Knowledge Engineering of National Education MinistryCollege of Computer Science and TechnologyJilin University Changchun China College of Information Engineering Guanghua College of Changchun University Changchun China College of Communications Engineering Jilin University Changchun China

ISBN: (纸本)9781424499533

In this paper, we propose PSOfold, a particle swarm optimization for RNA secondary structure prediction. PSOfold is b.sed on the recently pub.ished IPSO. We present two strategies to improve the performance of IPSO. Firstly, in order to b.ost the competence in searching an optimal solution, fuzzy logic control is used to adaptively adjust the parameters in PSO. Accordingly, three fuzzy logic controls are designed b. which the inertia weight, learning factors and the numb.r of ants are tuned respectively. Secondly, to further settle the stem permutation prob.em, we put forward a solution conversion strategy (SCS), which can transform discrete values of stems into an ordered stem comb.nation, thereb. supplying an enhanced solution to evaluation of ob.ective function. An evaluation of the performance of PSOfold in terms of prediction accuracy is made via comparison with one dynamic programming algorithm mfold and four metaheuristics, IPSO, ACRNA, RnaPredict, SARNA-Predict and mfold for ten individual known structures. PSOfold is ab.e to predict structures with higher prediction accuracy than the other metaheuristic b.sed methods on certain sequences, and has comparab.e performance compared with mfold. © 2011 IEEE.

关键词： Particle swarm optimization (PSO)

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