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检索条件"任意字段=International Conference of Soft Computing and Pattern Recognition"

共 7533 条记录，以下是311-320 订阅

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Acquisition of a Peristaltic Crawling Robot's Motion pattern Using Reinforcement Learning

Acquisition of a Peristaltic Crawling Robot's Motion Pattern...

引用

6th international conference on soft computing and Intelligent Systems (SCIS) / 13th international Symposium on Advanced Intelligence Systems (ISIS)

作者： Tesen, Satoshi Dobashi, Hiroki Saga, Norihiko Nagase, Jun-ya Kwansei Gakuin Univ Dept Human Syst Interact 2-1 Gakuen Sanda Hyogo 6691337 Japan Ryukoku Univ Dept Mech & Syst Engn Shiga 5202194 Japan

ISBN: (纸本)9781467327435;9781467327428

In disaster areas, rescue work by humans is extremely difficult. Therefore, rescue work using rescue robots in place of humans is attracting attention. This study specifically examines peristaltic crawling, the movement mechanism of an earthworm, because it can enable movement through narrow spaces and because it can provide stable movement according to various difficult environments. We develop a robot using peristalsis characteristics and derive a robot motion pattern using Q-learning, a mode of reinforcement learning. Additionally, we confirmed the convergence to the most suitable solution by coordinating Q-learning parameters.

关键词： component Biomimetics Peristaltic crawling Q-learning

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Arabic On Line Characters recognition Using Improved Dynamic Bayesian Networks

Arabic On Line Characters Recognition Using Improved Dynamic...

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international conference on Multimedia computing and Systems (ICMCS)

作者： Tlemsani, Redouane Benyettou, Abdelkader Natl Inst Telecommun Informat Technol & Commun IN Transmiss Dept Oran Algeria Univ Sci & Technol Dept Comp Sci Oran Algeria

ISBN: (纸本)9781467315203

Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology. This system is a Markovien system which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data. Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesiens networks generalization to the dynamic processes. Among our objective, amounts finding better parameters which represent the links (dependences) between dynamic network variables. In applications in pattern recognition, one will carry out the fixing structure which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory data base: NOUN. A neural tester proposed for DBN external optimization.

关键词： arabic on line character recognition pattern recognition dynamic bayesian network

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A spiking neural network that extracts frequent symbol patterns from time-series data with different symbol appearance intervals 12

A spiking neural network that extracts frequent symbol patte...

引用

Joint 12th international conference on soft computing and Intelligent Systems / 23rd international Symposium on Advanced Intelligent Systems (SCIS and ISIS)

作者： Morita, Kenta Morita, Naoki Suzuka Univ Med Sci Fac Med Engn Tsu Mie Japan Tokai Univ Sch Informat Telecommun Engn Tokyo Japan

ISBN: (纸本)9781665499248

In this research, we aim to extract frequent symbol patterns from symbol sequences. In the target time series data, the appearance timing of symbols is different. The purpose is to absorb the deviation of the appearance timing and extract frequent symbol patterns. This paper proposes a spiking neural network that extracts frequent symbol patterns. The structure of the proposed network grows automatically each time a symbol is given. By learning the network, the output unit will only fire when given a frequent symbol pattern, and the network will extract the frequent symbol patterns. As a result of a simple experiment, it was confirmed that the proposed network can extract frequent symbol patterns from the target time series data.

关键词： Spiking neural network Time-series information processing pattern mining

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Gaussian mixture pdf in one-class classification:: computing and utilizing confidence values

Gaussian mixture pdf in one-class classification:: computing...

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18th international conference on pattern recognition (ICPR 2006)

作者： Ilonen, J. Paalanen, P. Kamarainen, J. -K. Kalviainen, H. Lappeenranta Univ Technol Dept Informat Technol POB 20 FI-53851 Lappeenranta Finland

ISBN: (纸本)0769525210

In this study a confidence measure for probability density functions (pdfs) is presented. The measure can be used in one-class classification to select a pdf threshold for class inclusion. In addition, confidence information can be used to verify correctness of a decision in a multi-class case where for example the Bayesian decision rule reveals which class is the most probable. Additionally, using confidence values - which represent in which quantile of the probability mass a pdf value resides ([0, 1]) - is often straightforward compared to using arbitrarily scaled pdf values. As the main contributions, use of confidence information in classification is described and a method for confidence estimation is presented.

关键词： pattern recognition

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GA-Based Attempts to Improve the recognition Rate and Generalization Capacity of the Nonlinear soft Margin Support Vector Machines 18

GA-Based Attempts to Improve the Recognition Rate and Genera...

引用

18th international conference on System Theory, Control and computing (ICSTCC)

作者： State, Luminita Cocianu, Catalina Mircea, Marinela Univ Pitesti Dept Math & Informat Pitesti Romania Bucharest Univ Econ Studies Dept Informat & Cybernet Bucharest Romania

ISBN: (纸本)9781479946013

The aim of the paper is to report a new method based on genetic computation of designing a nonlinear soft margin SVM yielding to significant improvements in discriminating between two classes. The design of the SVM is performed in a supervised way, in general the samples coming from the classes being nonlinearly separable. The experimental analysis was performed on artificially generated data as well as on Ripley and MONK's datasets reported in the fourth section of the paper. The tests proved real improvements of both the recognition rate and generalization capacities without significantly increasing the computational complexity.

关键词： machine learning non-linear support vector machines soft margin SVM genetic algorithm kernel functions classifier design and evaluation model-free learning data driven control of parameters

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Campus Parking Space Allocation Distribution Using pattern Search and Particle Swarm pattern Search Algorithms 7

Campus Parking Space Allocation Distribution Using Pattern S...

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Joint 7th international conference on soft computing and Intelligent Systems (SCIS) and 15th international Symposium on Advanced Intelligent Systems (ISIS)

作者： Adewumi, Aderemi O. Joel, Luke O. Sawyerr, Babatunde A. Univ KwaZulu Natal Sch Math Stat & Comp Sci Westville Campus Durban South Africa

ISBN: (纸本)9781479959556

The problem of inadequate allocation of car parking spaces to users in the campus environment is a major concern for planning managers and traffic engineers. Parking users could prefer either reserved spaces or unreserved spaces. This makes the campus parking manager to be faced with two basic problems which are: the problem of allocating the actual number of available reserved spaces to users without any conflict over the same parking space, and the problem of determining the number of parking permit to be issued for parking lot with unreserved spaces. Hence, this paper investigates the use of two heuristic algorithms, pattern search(PS) algorithm and Particle swarm pattern search (PSwarm) algorithm, on the model for allocating car parking spaces in the university environment with an improvement in the constraints. The results obtained shows that the hybrid algorithm, particle swarm pattern search, outperforms the pattern search algorithm.

关键词： automobiles educational institutions particle swarm optimisation search problems traffic control PSwarm algorithm campus parking manager campus parking space allocation distribution car parking space allocation heuristic algorithm parking lot parking permit particle swarm pattern search algorithm reserved spaces university environment unreserved spaces Buildings Educational institutions Equations Linear programming Mathematical model Particle swarm optimization Resource management

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soft Margin SVM Modeling for Handling Imbalanced Human Activity Datasets in Multiple Homes

Soft Margin SVM Modeling for Handling Imbalanced Human Activ...

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international conference on Multimedia computing and Systems (ICMCS)

作者： Abidine, M'hamed Bilal Yala, Nawel Fergani, Belkacem Clavier, Laurent USTHB Fac Elect & Comp Sci Speech Commun & Signal Proc Lab Algiers Algeria Telecom LILLE Inst Mines Telecom IRCICA IEMNCNRSUMR 8520 Lille France

ISBN: (纸本)9781479938247

Activity recognition datasets are generally imbalanced, meaning certain activities occur more frequently than others. Not incorporating this class imbalance results in an evaluation that may lead to disastrous consequences for elderly persons. In this work, we evaluate various types of resampling methods: at algorithmic level using CS-SVM and at data level using SMOTE-CSVM and OS-CSVM combined with the discriminative classifier named soft-Margin Support Vector Machines (CSVM) in order to handle imbalanced data problem. We conduct several experiments using three real world activity recognition datasets and show that the SMOTE-CSVM and OS-CSVM are able to surpass CRF, CSVM and CS-SVM. OS-CSVM is slightly better than SMOTE-CSVM for classifying the activities using binary and ubiquitous sensors.

关键词： Activity recognition SVM Cost Sensitive Learning Machine Learning Imbalanced Data

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Constrained-MSER Detection of Retinal Pathology

Constrained-MSER Detection of Retinal Pathology

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21st international conference on pattern recognition (ICPR)

作者： San, Gilbert Lim Yong Lee, Mong Li Hsu, Wynne Natl Univ Singapore Singapore 117548 Singapore

ISBN: (纸本)9784990644109;9781467322164

With the increase in age and diabetes-related eye diseases, there is a rising demand for systems which can efficiently screen and locate abnormalities in retinal images. In this paper, we propose a framework that utilizes a variant of the Maximally Stable Extremal Region method, termed C-MSER, to systematically detect various retinopathy pathologies such as microaneurysms, haemorrhages, hard exudates and soft exudates. Experiments on three real-world datasets show that C-MSER is effective for online screening of diabetic retinopathy.

关键词： pattern recognition

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Towards Efficient Closed pattern Mining from Distributed Multi-Relational Data 7

Towards Efficient Closed Pattern Mining from Distributed Mul...

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Joint 7th international conference on soft computing and Intelligent Systems (SCIS) and 15th international Symposium on Advanced Intelligent Systems (ISIS)

作者： Kamiya, Yohei Seki, Hirohisa Nagoya Inst Technol Dept Comp Sci Nagoya Aichi 4668555 Japan

ISBN: (纸本)9781479959556

We consider closed pattern mining from distributed multi-relational databases, especially focusing on its efficient implementation. Given a set of local databases (horizontal partitions), we first compute their sets of closed patterns (concepts) using a closed pattern mining algorithm tailored to multi-relational data mining (MRDM). We then generate the set of closed patterns in the global database by utilizing the merge (or subposition) operator, studied in the field of Formal Concept Analysis. Since the computational complexity of MRDM increases compared with the conventional itemset mining, we propose some methods for improving the overall computations. We also present some experimental results using a distributed computation environment based on the MapReduce framework, which shows the effectiveness of the proposed methods.

关键词： multi-relational data mining closed patterns merge (subposition) operator FCA distributed databases

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Discovering pattern of Onomatopoeia Used in Food Reviews

Discovering Pattern of Onomatopoeia Used in Food Reviews

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6th international conference on soft computing and Intelligent Systems (SCIS) / 13th international Symposium on Advanced Intelligence Systems (ISIS)

作者： Kato, Ayumi Fukazawa, Yusuke Mori, Taketoshi Univ Tokyo Grad Sch Interdisciplinary Informat Studies Tokyo Japan Univ Tokyo Sch Engn Tokyo Japan Univ Tokyo Grad Sch Med Tokyo Japan

ISBN: (纸本)9781467327435;9781467327428

In this paper, we investigated onomatopoeia usage pattern in food reviews by proposing LDA (Latent Dirichlet Allocation) based onomatopoeia usage pattern analysis model. We collected total 685 numbers of onomatopoeias which are distributed to 208 food categories from 3,581,808 food reviews of Japanese food review site Tabelog. From the experimental result, we found several patterns how the onomatopoeias are chosen. The onomatopoeia is chosen based on user's interest on the combination of {location of food, material of the food, cooking method} and {the texture of food, sound when eating, and looks of food people's status when eating the food}. In addition, we investigate how the precision of the clustering result changes depending on the N (number of onomatopoeia of each food categories). We found that the results of N=30 is better than one of N=100 as large number of onomatopoeia for each food categories like 100 is likely to include onomatopoeias that are irrelevant to food.

关键词： component onomatopoeia food review LDA term weighting new word discovery

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