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共 257 条记录，以下是81-90 订阅

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Geometrical feature based ranking using grey relational analysis (GRA) for writer identification

Geometrical feature based ranking using grey relational anal...

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international conference of soft computing and pattern recognition (socpar)

作者： Intan Ermahani A. Jalil Azah Kamilah Muda Siti Mariyam Shamsuddin Anca Ralescu Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka Malaysia Soft Computing Research Group Universiti Teknologi Malaysia Skudai Johor Malaysia School of Computing Sciences and Informatics University of Cincinnati Cincinnati Ohio

The author's unique characteristic is determined by the variation of generated features from feature extraction process. Different sets of features produced are based on different feature extraction methods (local or global). Thus, the process has led to the production of high dimensional datasets that contributing to many irrelevant or redundant features. The main problem however is to find a way to identify the most significant features. The features ranking method using Grey Relational Analysis (GRA) is proposed to find the significance of each feature and give ranking to the features. This study presents the Higher-Order United Moment Invariant (HUMI) as the global feature extraction methods. The combinations of features with the higher ranking are discretized and used as the subsets of features to identify the writer. The result demonstrates that the average classification accuracy of five classifiers by using just the combination of two most significant features have yielded a better performance than using all features.

关键词： Feature extraction Accuracy Handwriting recognition Niobium Hidden Markov models Text analysis

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Flock identification using connected components labeling for multi-robot shepherding

Flock identification using connected components labeling for...

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international conference of soft computing and pattern recognition (socpar)

作者： Sazalinsyah Razali Nurul Fathiyah Shamsudin Mashanum Osman Qinggang Meng Shuang-Hua Yang Faculty of Information & Communication Technology Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka Malaysia Department of Computer Science Loughborough University Leicestershire U.K.

Shepherding is often used in robotics and applied to various domains such as military in Unmanned Aerial Vehicle (UAV) or Unmanned Ground Vehicle (UGV) combat scenarios, disaster rescue and even in manufacturing. Generally, robot shepherding refers to a task of a robot known as shepherd or sheep herder, who guards and takes care of flocks of sheep, to make sure that the flock is intact and protect them from predators. In order to make an accurate decision, the shepherd needs to identify the flock that needs to be managed. How does the shepherd can precisely identify a group of animals as a flock? How can one actually judge a flock of sheep, is a flock? How does the shepherd decide how to approach or to steer the flock? These are the questions that relates to flock identification. In this paper, a new method using connected components labeling is proposed to cater the problem of flock identification in multi-robot shepherding scenarios. The results shows that it is a feasible approach, and can be used when integrated with the Player/Stage robotics simulation platform.

关键词： Accuracy Labeling Robots Image processing Testing pattern recognition Computational modeling

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Edge direction matrixes-based local binary patterns descriptor for invariant pattern recognition

Edge direction matrixes-based local binary patterns descript...

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international conference of soft computing and pattern recognition (socpar)

作者： Mohammed Ahmed Talab Siti Norul Huda Sheikh Abdullah Mohammad Hakim Assiddiq Razalan Faculty of Technology and Information Science Center for Artificial Intelligence Technology Bangi Selangor Malaysia Universiti Kebangsaan Malaysia Bangi Selangor MY

Invariant descriptor for shape and texture image recognition usage is an essential branch of pattern recognition. It is made up of techniques that aim at extracting information from shape images via human knowledge and works. The descriptors need to have strong Local Binary pattern (LBP) in order to encode the information distinguishing them. Local Binary pattern (LBP) ensures encoding global and local information and scaling invariance by introducing a look-up table to reflect the uniformity structure of an object. It is needed as the edge direction matrices (EDMS) only apply global invariant descriptor which employs first and secondary order relationships. The main objective of this paper is the need of improved recognition capabilities which achieved by the combining LBP and EDMS. Working together, these two descriptors will add advantages to the program and enable the researcher to investigate the weaknesses of each one. Two classifiers are used: multi-layer neural network and random forest. The techniques used in this paper are compared with Gray-Level Co-occurrence matrices (GLCM-EDMS) and Scale Invariant Feature Transform (SIFT) by using two benchmark dataset: MPEG-7 CE-Shape-1 for shape and Arabic calligraphy for texture. The experiments have shown the superiority of the introduced descriptor over the GLCM-EDMS and the SIFT.

关键词： Feature extraction Image edge detection pattern recognition Transform coding Training Shape Standards

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Paired feature constraints for latent dirichlet topic models

Paired feature constraints for latent dirichlet topic models

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international conference of soft computing and pattern recognition (socpar)

作者： Nagesh Bhattu Sristy D. V. L. N. Somayajulu R. B. V. Subramanyam Department of CSE NIT Warangal

Non Parametric Bayes models, so called family of Latent Dirichlet Allocation (LDA) Topic Models have found application in various aspects of pattern recognition like sentiment analysis, information retrieval, question answering etc. The topics induced by LDA are used for later tasks such as classification, regression(movie ratings), ranking and recommendation. Recently various approaches are suggested to improve the utility of topics induced by LDA using various side-information such as labeled examples and labeled features. Pair-Wise feature constraints such as cannot-link and must-link, represent weak-supervision and are prevalent in domains such as sentiment analysis. Though must-link constraints are relatively easier to incorporate by using dirichlet tree, the cannot-link constraints are harder to incorporate using the dirichlet forest. In this paper we proposed an approach to address this problem using posterior constraints. We introduced additional latent variables for capturing the constraints, and modified the gibbs sampling algorithm to incorporate these constraints. Our method of Posterior Regularization has enabled us to deal with both types of constraints seamlessly in the same optimization framework. We have demonstrated our approach on a product sentiment review data set which is typically used in text analysis.

关键词： Data models pattern recognition Analytical models Sentiment analysis Coherence Vocabulary Graphical models

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Cuckoo search algorithm for optimization problems - a literature review

Cuckoo search algorithm for optimization problems - a litera...

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4th international conference on Information Technology for Manufacturing Systems, ITMS 2013

作者： Mohamad, Azizah Zain, Azlan Mohd Bazin, Nor Erne Nazira Udin, Amirmudin Soft Computing Research Group Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia

ISBN: (纸本)9783037858783

Cuckoo Search (CS) is an optimization algorithm developed by Yang and Deb in 2009. This paper describes an overview of CS which is inspired by the life of a bird family, called Cuckoo as well as overview of CS applications in various categories for solving optimization problems. Special lifestyle of Cuckoo and their characteristics in egg laying and breeding has been the basic motivation for this optimization algorithm. The categories that reviewed are Engineering, pattern recognition, software Testing & Data Generation, Networking, Job Scheduling and Data Fusion and Wireless Sensor Networks. From the reviewed CS mostly applied in engineering area for solving optimization problems. The objective of this paper is to provide overview and summarize the review of application of the CS. © (2013) Trans Tech Publications, Switzerland.

关键词： software testing

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Cuckoo Search Algorithm for Optimization Problems——A literature Review

Cuckoo Search Algorithm for Optimization Problems——A liter...

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2013 4th international conference on Information Technology for Manufacturing Systems(ITMS 2013)

作者： Azizah Mohamad Azlan Mohd Zain Nor Erne Nazira Bazin Amirmudin Udin Soft Computing Research Group Faculty of Computing Universiti Teknologi Malaysia Faculty of Education Universiti Teknologi Malaysia

Cuckoo Search(CS) is an optimization algorithm developed by Yang and Deb in 2009. This paper describes an overview of CS which is inspired by the life of a bird family, called Cuckoo as well as overview of CS applications in various categories for solving optimization problems. Special lifestyle of Cuckoo and their characteristics in egg laying and breeding has been the basic motivation for this optimization algorithm. The categories that reviewed are Engineering, pattern recognition, software Testing & Data Generation, Networking, Job Scheduling and Data Fusion and Wireless Sensor Networks. From the reviewed CS mostly applied in engineering area for solving optimization problems. The objective of this paper is to provide overview and summarize the review of application of the CS.

关键词： Cuckoo Search Algorithm Optimization problem Levy flights Cuckoo

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Proceedings of the 2010 international conference of soft computing and pattern recognition, socpar 2010

Proceedings of the 2010 International Conference of Soft Com...

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2010 international conference of soft computing and pattern recognition, socpar 2010

ISBN: (纸本)9781424478958

The proceedings contain 86 papers. The topics discussed include: iris features extraction using dual-tree complex wavelet transform;fuzzy methods for forensic data analysis;a new weighted rough set framework for imbalance class distribution;multi stereo camera data fusion for fingertip detection in gesture recognition systems;recognition of signed expressions using visually-oriented subunits obtained by an immune-based optimization;3-D object recognition based on SVM and stereo-vision: application in endoscopic imaging;inter-camera color calibration for object re-identification and tracking;improving the accuracy of intrusion detection systems by using the combination of machine learning approaches;mining web videos for video quality assessment;ultra fast fingerprint indexing for embedded system;damageless image hashing using neural network;and classification by means of fuzzy analogy-related proportions - a preliminary report.

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Proceedings of the 2010 international conference of soft computing and pattern recognition, socpar 2010: Welcome message from socpar 2010 chairs

Proceedings of the 2010 International Conference of Soft Com...

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Proceedings of the 2010 international conference of soft computing and pattern recognition, socpar 2010 2010年 ii页

作者： Abraham, Ajith Prade, Henri Martin, Trevor Muda, Azah Kamilah Laurent, Anne

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Web mining application in university library personalized search engine

Web mining application in university library personalized se...

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2011 international conference of soft computing and pattern recognition, socpar 2011

作者： Zhao, Jing Department of Management Shanghai International Studies University Academy of Economic Trade Management Shanghai China

ISBN: (纸本)9781457711947

The article examines web mining application in university library search engine. It primarily researches the technology that is personal usage records track in web usage mining. It also discusses how to establish a university library personalized search engine system. The system studies user identification, user profile, user's interest model and user interest extraction. The article explains various processing modules of university library personalized search engine system. It designs university library personalized search engine system. It finally verifies that web mining has effect on searching web page ranking in university library. © 2011 IEEE.

关键词： Search engines

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Brief survey on image semantic analysis and understanding

Brief survey on image semantic analysis and understanding

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international conference of soft computing and pattern recognition (socpar)

作者： Zhao Xie Jun Gao Kewei Wu Jun Zhang School of Computer and Information Hefei University of Technology Hefei China

Semantic issues are highly concerned with high-level interpretation in image understanding, which include text-image gap and its own affinity. Concentrating on text-formatting with entities in images, three sophisticated methodologies are roundly reviewed as generative, discriminative and descriptive grammar on the basis of contextual features. The following objective benchmark for visual words is also directly presented for semantic coherency. Finally, the summarized directions on semantics in image understanding are discussed intensively for further researches.

关键词： Semantics Visualization Computational modeling pattern recognition Educational institutions Computer vision Benchmark testing

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