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第35届中国控制会议

作者： LI Haifeng HU Zunhe CHEN Xinwei College of Computer Science and Technology Civil Aviation University of China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Department of Computer Science Minjiang University

ISBN: (纸本)9781509009107

A robust optical flow-based visual odometry method using a single onboard camera is proposed in this *** improve the quality of the noisy optical flows,a correction method across multiple frames is ***,the optical flows in the plane at infinity are detected and removed as these optical flows have very low signal to noise ratio for robot translation ***,a RANSAC approach for robot ego-motion estimation is *** experiments are carried out and the results show that the proposed method is able to estimate the camera trajectory robustly with reasonable accuracy.

关键词： visual odometry optical flows mobile robot

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Variational neural discourse relation recognizer

Variational neural discourse relation recognizer

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2016 Conference on Empirical Methods in Natural Language processing, EMNLP 2016

作者： Zhang, Biao Xiong, Deyi Su, Jinsong Liu, Qun Ji, Rongrong Duan, Hong Zhang, Min Xiamen University Xiamen361005 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China ADAPT Centre School of Computing Dublin City University Ireland Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781945626258

Implicit discourse relation recognition is a crucial component for automatic discourse-level analysis and nature language understanding. Previous studies exploit discriminative models that are built on either powerful manual features or deep discourse representations. In this paper, instead, we explore generative models and propose a variational neural discourse relation recognizer. We refer to this model as VarNDRR. VarNDRR establishes a directed probabilistic model with a latent continuous variable that generates both a discourse and the relation between the two arguments of the discourse. In order to perform efficient inference and learning, we introduce neural discourse relation models to approximate the prior and posterior distributions of the latent variable, and employ these approximated distributions to optimize a reparameterized variational lower bound. This allows VarNDRR to be trained with standard stochastic gradient methods. Experiments on the benchmark data set show that VarNDRR can achieve comparable results against state-of-the-art baselines without using any manual features. © 2016 Association for Computational Linguistics

关键词： Gradient methods

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An object classification method based on the improved bacterial foraging optimisation algorithm

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International Journal of Wireless and Mobile Computing 2017年第2期12卷 166-173页

作者： Zeng, Zhigao Guan, Lianghua Yi, Shengqiu Zhu, Yanhui Liu, Qiang Tong, Qi Zeng, Sanyou College of Computer and Communication Hunan University of Technology Hunan412007 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory Hunan China Department of Computer Science China University of GeoSciences Wuhan Hubei China

This paper proposes a new object classification method based on an improved bacterial foraging optimisation algorithm. Firstly, a dynamic step size is used instead of the fixed step size of the chemotaxis. Secondly, the fixed elimination-dispersal probability is replaced by the dynamic probability. Features are extracted to distinguish the objects, such as pedestrians, cars and pets. Ultimately, all the objects are classified using the improved bacterial foraging optimisation algorithm. The experimental results prove that the effectiveness of the object classification method proposed in this paper is better than that of other algorithms. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Optimization

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Research on entity relation extraction in TCM acupuncture and moxibustion field

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Journal of information Hiding and Multimedia Signal processing 2017年第2期8卷 358-367页

作者： Sun, Shuihua Huang, Degen Zhang, Jing School of Computer Science and Technology Dalian University of Technology Dalian116024 China College of Information Science and Engineering Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China

For the context of entity relation instance in TCM acupuncture and moxibustion field, effective words, syntax and semantics features are chosen to combine into feature template, and the entity relation instances are vectorized. The classification models of entity relations in TCM acupuncture and moxibustion area are trained by the machine learning method which is based on support vector machine. The experimental results show that the feature template of entity relations in this thesis have excellent effects on the entity relation extraction in TCM acupuncture and moxibustion area. The F-measure of entity relation classification model of DM, HM, AM and DRM reached 93.25%, 87.19%, 86.57%and84.57% respectively. © 2017 ISSN.

关键词： Support vector machines

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Construction of the recognition model for trigger words of Chinese acupuncture and moxibustion events

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Journal of information Hiding and Multimedia Signal processing 2017年第6期8卷 1283-1293页

The recognization of trigger words for Chinese acupuncture and moxibustion events is a key step in the extraction of Chinese acupuncture and moxibustion events. It plays an important role in knowledge mining in the field of Chinese acupuncture and moxibustion. This paper extracts the manually annotated trigger words from the training corpus, constructs the table of trigger words for Chinese acupuncture and moxibustion events, then expands this table with the Tongyici Cilin (Chinese thesaurus), and identifies the candidate trigger words for Chinese acupuncture and moxibustion events based on the extended trigger word table;and then according to characteristics of the expressions in the field of Chinese acupuncture and moxibustion, this paper prepares the filtering rules for candidate trigger words for Chinese acupuncture and moxibustion events. This paper uses the above techniques to construct the recognition model of trigger words for Chinese acupuncture and moxibustion events that integrates dictionary matching and rule-based filtering. The results of the experiment show that this model has a good trigger word recognition function, and F-measure of trigger words recognition for the cure and health events reaches 88.28% and 34.15% respectively. © 2017, Ubiquitous International. All rights reserved.

关键词： Vocabulary control

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Nuclear norm regularized coding with local position-patch and nonlocal similarity for face hallucination

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Digital Signal processing 2017年 64卷 107-120页

作者： Guangwei Gao Jian Yang Zhihui Lai Pu Huang Jielin Jiang Hao Gao Dong Yue Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing 210023 PR China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou 350121 PR China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 PR China College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 PR China Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing 210094 PR China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 PR China

Learning-based face hallucination methods have received much attention and progress in past few decades. Specially, position-patch based approaches have been proposed to replace the probabilistic graph-based or manifold learning-based ones. As opposed to the existing patch based methods, where the input image patch matrix is converted into vectors before combination coefficients calculation, in this paper, we propose to directly use the image matrix based regression model for combination coefficients computation to preserve the essential structural information of the input patch matrix. For each input low-resolution (LR) patch matrix, its combination coefficients over the training image patch matrices at the same position can be computed. Then the corresponding high-resolution (HR) patch matrix can be obtained with the LR training patches replaced by the corresponding HR ones. The nonlocal self-similarities are finally utilized to further improve the hallucination performance. Various experimental results on standard face databases indicate that our proposed method outperforms some state-of-the-art algorithms in terms of both visual quantity and objective metrics.

关键词： Face hallucination Position-patch Matrix based regression Nuclear norm Nonlocal similarity

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Combining Event-level and Cross-event Semantic information for Event-Oriented Relation Classification by SCNN

Combining Event-level and Cross-event Semantic Information f...

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第十五届全国计算语言学学术会议(CCL2016)暨第四届基于自然标注大数据的自然语言处理国际学术研讨会(NLP-NABD-2016)

作者： Siyuan Ding Yu Hong Shanshan Zhu Jianmin Yao Qiaoming Zhu Provincial Key Laboratory of Computer Information Processing Technology Soochow UniversitySuzhouChina

Previous researches on event relation classification primarily rely on lexical and syntactic *** this paper,we use a Shallow Convolutional Neural Network(SCNN)to extract event-level and cross-event semantic features for event relation *** the one hand,the shallow structure alleviates the over-fitting problem caused by the lack of diverse relation *** the other hand,the utilization and combination of event-level and cross-event semantic information help improve relation *** experimental results show that our approach outperforms the state of the art.

关键词： Event Relation Classification Semantic information Frame Embedding SCNN

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A novel image segmentation method based on an improved bacterial foraging optimization algorithm

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Journal of information Hiding and Multimedia Signal processing 2017年第2期8卷 348-357页

作者： Zeng, Zhi Gao Guan, Liang Hua Zhu, Yan Hui Liu, Qiang He, Jin Rong College of Computer and Communication Hunan University of Technology ZhuzhouHunan412000 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory China College of Information Engineering Northwest A and F University YanglingShaanxi Province712100 China

When some bionic optimization algorithms are used for image segmentation, we find that the search speeds of these algorithms are slow and the local searching abilities of these algorithms need be improved. In order to solve these problems, this paper proposed a new image segmentation method based on the improved bacterial foraging optimization algorithm. Firstly, a dynamic step size is used to instead of the fixed step size of the chemotaxis operator, and a dynamic probability is used to instead of the fixed probability of elimination-dispersal operator. Then, the gray histograms of the images are extracted for the image segmentation. Ultimately, the images are segmented using the improved bacterial foraging optimization algorithm. The image segmentation results show that the accuracy and the speed of the image segmentation based on the improved bacterial foraging optimization algorithm are superior to the ones that based on others traditional bionic optimization algorithms. © 2017 ISSN.

关键词： Image segmentation

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Research on Ship Automatic Modeling and Identification System

Research on Ship Automatic Modeling and Identification Syste...

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2017 2nd International Conference on Mechatronics and information technology(ICMIT 2017)

作者： Yao-jie Chen Xin Yuan Shu-lin Du Can Song School of Computer Science and Technology Wuhan University of Science and Technology School of Navigation Wuhan University of Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System

When the ship sails in different water situation, it is necessary to forecast the movement state of the ship according to the real-time ship motion state parameters. The traditional method uses the classical MMG(mathematical model group) three-degree-of-freedom motion mathematical model to predict the modeling. For the existence of less detection parameters, the error is relatively large, the accuracy is not enough and so on. In this paper, a six-degree-of-freedom ship motion model based on sway, surge, heave, roll, pitch and yawing is proposed, combined with the least square method to achieve the automatic identification modeling method. Using this method, according to the GPS inertial navigation and positioning module to collect the data to simulate, and contrast with the traditional modeling method. The experimental results show that the improved automatic identification modeling method has better effect than the traditional modeling method, which greatly improves the accuracy of ship motion prediction.

关键词： automatic identification six degrees of freedom least square method

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A throughput aware with collision-free MAC for wireless LANs

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Science China(information Sciences) 2016年第2期59卷 240-242页

作者： Tingrui PEI Yafeng DENG Zhetao LI Gengming ZHU Gaofeng PAN Youngjune CHOI Hiroo SEKIYA College of Information Engineering Xiangtan University Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University School of Computer Science & Engineering Hunan University of Science and Technology School of Electronic and Information Engineering Southwest University Department of Information and Computer Engineering Ajou University Graduate School of Advanced Integration Science Chiba University

Dear editor,The Carrier Sense Multiple Access with Collision Avoidance(CSMA/CA)hybrid with the resource reservation approach from Time Division Multiple Address(TDMA)has been emerged as a promising method to solve collision problems in wireless LANs[1–6].In the hybrid method,a TDMA circle contains multiple slots for nodes to contend for the ***,it allows a

关键词： MAC CSCF free TDMA A throughput aware with collision-free MAC for wireless LANs

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