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Congress on Image and Signal processing, CISP

作者： Li Zhang Er-yong Wu School of Computer Science Hangzhou Dianzi University Hangzhou China Zhejiang Provincial Key Laboratory of Information Network Technology University of Zhejiang Hangzhou China

By analyzing the characteristics of off-road images, a new and computationally efficient algorithm of road segmentation and road type identification for autonomous land vehicle (ALV) navigation system based on the proposed new-type histogram calculation was established. The new-type histogram is a new image, not a curve. It is also directional. It makes a statistic of the pixels under some special direction. With the histogram images, each pixel in the original image is given a threshold separately, thus the road images are correctly segmented. Moreover, the new-type histogram image could be used to identify road type. It avoids the deficiency that road images are wrongly segmented by reason that the preset road model does not fit in the real scene in the conventional methods. The proposed method does not need any extraction of the relevant information in the image (texture of the road, shadows, road edges, etc.). The method is evaluated on thousands of the cross-country road images under various lighting conditions. The experimental results demonstrate the method's accuracy, feasibility and robustness. It increases the segmentation accuracy to an extent. This would be a potentially significant contribution to the active area of road segmentation in the ALV navigation system.

关键词： Histograms Roads Image segmentation Navigation Image analysis Algorithm design and analysis Land vehicles Statistics Pixel Layout

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Novel contour-feature retrieval algorithm

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Guangdianzi Jiguang/Journal of Optoelectronics Laser 2009年第1期20卷 108-112页

作者： Sun, Jun-Ding Li, Quan-Xi Wu, Xiao-Sheng School of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Provincial Key Laboratory of Computer Information Processing Technology Suzhou University Suzhou 215006 China

The paper presents a novel approach for contour-based shape retrieval. The contour is firstly sampled and smoothed by a Gaussian filter. Then, the sampled points are classified into salient (convex or concave) or smooth type points by their internal angles. In addition to distance histograms (DH), two new descriptors named relative address distribution (RAD) and relative unit entropy (RUE) are introduced to describe the correlation of each type of contour points. These descriptors have powerful descriptive ability for contour with more spatial information. Comparisons are conducted between the proposed method and several other feature descriptors. The results show that the new method is efficient and it provides noticeable improvement to the performance of shape retrieval.

关键词： Entropy

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Interested Sample Point Pre-Selection Based Dense Terrain Reconstruction for Autonomous Navigation

Interested Sample Point Pre-Selection Based Dense Terrain Re...

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International Symposium on Intelligent information technology Application, IITA

作者： Lili Lin Wenhui Zhou College of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou China Zhejiang Provincial Key Laboratory of Information Network Technology University of Zhejiang Hangzhou China College of Computer and Software Hangzhou Dianzi University Hangzhou China

This paper addresses the problem of terrain reconstruction for autonomous navigation. Dense stereo matching based terrain reconstruction methods are sensitive to mismatch pixels in disparity map, and consume lots of computation on pixels in uninterested regions. Traditional sample point pre-selection methods (SPPS) are effective, but they can only obtain sparse terrain map for grid-based representation. We extend the idea of SPPS methods and propose an interested sample point pre-selection (ISPPS) based dense reconstruction method. In this method, we choose appropriate interested sample points and set their reconstruction results as local control points, which can reduce the ambiguity and computation complexity in successive dense reconstruction procedures. The most prominent advantage of this method is it directly recovers the 3D terrain model without dense disparity map. Experiments show the proposed method is robust, and can achieve precise dense reconstruction with low computation complexity.

关键词： Navigation Image reconstruction Reconstruction algorithms Stereo image processing Educational institutions Robustness Interpolation Robot kinematics Space exploration Grid computing

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Multivariate classification of deep web sources based on maximum entropy model

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Journal of Computational information Systems 2008年第3期4卷 1093-1100页

作者： Huang, Li Zhao, Pengpeng Cui, Zhiming Wei, Fang Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China

With the fast development of World Wide Web, the quantity of web information is increasing in an unprecedented pace, a great many of which are generated dynamically from background databases, and can't be indexed by traditional search engine, so we call them Deep Web. For the heterogeneous and dynamic features of Deep Web sources, classifying the Deep Web source by domain effectively is a significant precondition of Deep Web sources integration. In this paper, we consider the visible features of Deep Web and Maximum Entropy approach, and then on the basis of binary classification, we propose a new multivariate classification approach based on Maximum Entropy towards Deep Web sources. In addition, we propose a Feedback algorithm to improve the accuracy of classification. An experimental evaluation over real Web data shows that, our approach could provide an effective and general solution to the multivariate classification of Deep Web sources.

关键词： Search engines

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Automated essay scoring using the KNN algorithm

Automated essay scoring using the KNN algorithm

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International Conference on computer Science and Software Engineering, CSSE 2008

作者： Bin, Li Jun, Lu Jian-Min, Yao Qiao-Ming, Zhu Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China

ISBN: (纸本)9780769533360

The K-Nearest Neighbor (KNN) algorithm for text categorization is applied to CET4 essays. In this paper, each essay is represented by the Vector Space Model (VSM). After removing the stop words, we chose the words, phrases and arguments as features of the essays, and the value of each vector is expressed by the term frequency and inversed document frequency (TF-IDF) weight. The TF and information fain (IG) methods are used to select features by predetermined thresholds. We calculated the similarity of essays with cosine in the KNN algorithm. Experiments on CET4 essays in the Chinese Learner English Corpus (CLEC) show accuracy above 76% is achieved. © 2008 IEEE.

关键词： Text processing

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Implementation of data-exchanging system based on message oriented middleware in agricultural website

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WSEAS Transactions on computers 2008年第6期7卷 620-629页

作者： Zhang, Xiaoshuan Wu, Qinghua Tian, Dong Zhao, Ming Xiaoshuan, Zhang College of Information and Electrical Engineering China Agricultural University Beijing 100083 China Jiangsu Provincial Key Laboratory Computer Information Processing Technology Suzhou China

With the startup of the Golden Agriculture Project, the step of being-information of agriculture is becoming rapid. And the transformation and share of data is indispensable to the being-information of agriculture. How to implement data combination, data transformation and data receiving applications are the important means to complete the information share safely and enhance the efficiency. The paper starts with searching of methods to implement data interchange, and introduce some of the methods, points of the techniques, etc. Basing on this, the paper also introduces the detail requirement analyses, system design and detail implementation of the system. According to the requirement and trait of the project, a data interchange system is researched and completed. And a data interchange model based on message-oriented middleware (MOM) is presented in this paper, which builds a middleware between the province and the ministry taking part in data interchange. The system has traits as follows: 1. keeping the data safe and credible while it is transformed. 2. having excellent transplantable and applied capability. 3. doesn't need intervention of workman in the process of data interchange. 4. applying the data interchange between databases of different structure. 5. being simple to be developed and applied. MOM TongLink/Q offers interfaces for application development, and it completes the data transformation through the internet. The integration adapters developed do the data management, which are developed based on the Frame for Applications Integration TongIntegrator. This method offers a new approach to resolve the question of data interchange. Now the system has been successfully applied in the data interchange project of Ministry of Agriculture.

关键词： Electronic data interchange

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Dependency tree-based SRL with proper pruning and extensive feature engineering

Dependency tree-based SRL with proper pruning and extensive ...

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12th Conference on Computational Natural Language Learning, CoNLL 2008

作者： Wang, Hongling Wang, Honglin Zhou, Guodong Zhu, Qiaoming Jiang Su Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow University Suzhou 215006 China

ISBN: (纸本)1905593481

This paper proposes a dependency tree-based SRL system with proper pruning and extensive feature engineering. Official evaluation on the CoNLL 2008 shared task shows that our system achieves 76.19 in labeled macro F1 for the overall task, 84.56 in labeled attachment score for syntactic dependencies, and 67.12 in labeled F1 for semantic dependencies on combined test set, using the standalone MaltParser. Besides, this paper also presents our unofficial system by 1) applying a new effective pruning algorithm;2) including additional features;and 3) adopting a better dependency parser, MSTParser. Unofficial evaluation on the shared task shows that our system achieves 82.53 in labeled macro F1, 86.39 in labeled attachment score, and 78.64 in labeled F1, using MSTParser on combined test set. This suggests that proper pruning and extensive feature engineering contributes much in dependency tree-based SRL. © 2008.

关键词： Semantics

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Semi-Supervised Learning for Relation Extraction 3

Semi-Supervised Learning for Relation Extraction

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3rd International Joint Conference on Natural Language processing, IJCNLP 2008

作者： Zhou, Guo Dong Li, Jun Hui Qian, Long Hua Zhu, Qiaoming Jiangsu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow Univ. Suzhou215006 China

This paper proposes a semi-supervised learning method for relation extraction. Given a small amount of labeled data and a large amount of unlabeled data, it first bootstraps a moderate number of weighted support vectors via SVM through a co-training procedure with random feature projection and then applies a label propagation (LP) algorithm via the bootstrapped support vectors. Evaluation on the ACE RDC 2003 corpus shows that our method outperforms the normal LP algorithm via all the available labeled data without SVM bootstrapping. Moreover, our method can largely reduce the computational burden. This suggests that our proposed method can integrate the advantages of both SVM bootstrapping and label propagation.s. © 2008 IJCNLP 2008 - 3rd International Joint Conference on Natural Language processing, Proceedings of the Conference. All rights reserved.

关键词： Extraction

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Context-Sensitive Convolution Tree Kernel for Pronoun Resolution 3

Context-Sensitive Convolution Tree Kernel for Pronoun Resolu...

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3rd International Joint Conference on Natural Language processing, IJCNLP 2008

作者： Zhou, GuoDong Kong, Fang Zhu, Qiaoming JiangSu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow Univ. Suzhou215006 China

This paper proposes a context-sensitive convolution tree kernel for pronoun resolution. It resolves two critical problems in previous researches in two ways. First, given a parse tree and a pair of an anaphor and an antecedent candidate, it implements a dynamic-expansion scheme to automatically determine a proper tree span for pronoun resolution by taking predicate- and antecedent competitor-related information into consideration. Second, it applies a context-sensitive convolution tree kernel, which enumerates both context-free and context-sensitive sub-trees by considering their ancestor node paths as their contexts. Evaluation on the ACE 2003 corpus shows that our dynamic-expansion tree span scheme can well cover necessary structured information in the parse tree for pronoun resolution and the context- sensitive tree kernel much outperforms previous tree kernels. © 2008 IJCNLP 2008 - 3rd International Joint Conference on Natural Language processing, Proceedings of the Conference. All rights reserved.

关键词： Convolution

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Exploiting constituent dependencies for tree kernel-based semantic relation extraction

Exploiting constituent dependencies for tree kernel-based se...

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22nd International Conference on Computational Linguistics, Coling 2008

作者： Qian, Longhua Zhou, Guodong Kong, Fang Zhu, Qiaoming Qian, Peide Jiangsu Provincial Key Lab. for Computer Information Processing Technology School of Computer Science and Technology Soochow University 1 Shizi Street Suzhou 215006 China

ISBN: (纸本)9781905593446

This paper proposes a new approach to dynamically determine the tree span for tree kernel-based semantic relation extraction. It exploits constituent dependencies to keep the nodes and their head children along the path connecting the two entities, while removing the noisy information from the syntactic parse tree, eventually leading to a dynamic syntactic parse tree. This paper also explores entity features and their combined features in a unified parse and semantic tree, which integrates both structured syntactic parse information and entity-related semantic information. Evaluation on the ACE RDC 2004 corpus shows that our dynamic syntactic parse tree outperforms all previous tree spans, and the composite kernel combining this tree kernel with a linear state-of-the-art feature-based kernel, achieves the so far best performance. © 2008. Licensed under the Creative Commons.

关键词： Semantics

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