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检索条件"任意字段=International Conference on Soft Computing and Pattern Recognition, SoCPaR 2009"

共 257 条记录，以下是211-220 订阅

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Arrhythmia Beat Classification Using Pruned Fuzzy K-Nearest Neighbor Classifier

Arrhythmia Beat Classification Using Pruned Fuzzy K-Nearest ...

引用

international conference of soft computing and pattern recognition (socpar)

作者： M. Arif M. U. Akram F. A. Afsar Department of Electrical Engineering Air University Islamabad Pakistan Elixir technologies Pakistan Private Limited Islamabad Pakistan Department of Computer & Information Sciences PIEAS Islamabad Pakistan

In this paper, pruned fuzzy k-nearest neighbor (PFKNN) classifier is proposed to classify different types of arrhythmia beats present in the MIT-BIH Arrhythmia database. We have tested our classifier on ~103100 beats for six beat types present in the database. Fuzzy KNN (FKNN) can be implemented very easily but large number of training examples used for classification which can be very time consuming and requires large storage space. Hence, we have proposed a time efficient pruning algorithm especially suitable for FKNN which can maintain good classification accuracy with appropriate retained ratio of training data. By using the pruning algorithm with Fuzzy KNN, we have achieved beat classification accuracy of 97% and geometric mean of sensitivity is 94.5% with only 19% of the total training examples. The accuracy and sensitivity is comparable to FKNN when all the training data is used.

关键词： Electrocardiography Electronic mail Databases Training data Decision support systems Feature extraction Wavelet analysis Neural networks Fuzzy logic pattern recognition

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BiSim: A Simple and Efficient Biclustering Algorithm

BiSim: A Simple and Efficient Biclustering Algorithm

引用

international conference of soft computing and pattern recognition (socpar)

作者： Nighat Noureen Muhammad Abdul Qadir Department of Computer Science & Bioinformatics Mohammad Ali Jinnah University Islamabad Pakistan

Analysis of gene expression data includes classification of the data into groups and subgroups based on similar expression patterns. Standard clustering methods for the analysis of gene expression data only identifies the global models while missing the local expression patterns. In order to identify the missed patterns biclustering approach has been introduced. Various biclustering algorithms have been proposed by scientists. Among them binary inclusion maximal algorithm (BiMax) forms biclusters when applied on a gene expression data through divide and conquer approach. The worst-case running-time complexity of BiMax for matrices containing disjoint biclusters is O(nmb) and for arbitrary matrices is of order O(nmb min{n, m}) where b is the number of all inclusion-maximal biclusters in matrix. In this paper we present an improved algorithm, BiSim, for biclustering which is easy and avoids complex computations as in BiMax. The complexity of our approach is O(n*m) for n genes and m conditions, i.e, a matrix of size n*m. Also it avoids extra computations within the same complexity class and avoids missing of any biclusters.

关键词： Gene expression Clustering methods Clustering algorithms pattern analysis Cells (biology) Biological processes pattern recognition Computer science Bioinformatics Algorithm design and analysis

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3D Volumetric CT Liver Segmentation Using Hybrid Segmentation Techniques

3D Volumetric CT Liver Segmentation Using Hybrid Segmentatio...

引用

international conference of soft computing and pattern recognition (socpar)

作者： Wan Nural Jawahir Wan Yussof Hans Burkhardt Pattern Recognition and Image Processing Albert Ludwigs University of Freiburg Freiburg im Breisgau Germany

The first step for computer-aided diagnosis for liver of CT scans is the identification of liver region. To deal with multislice CT scans, automatic liver segmentation is required. In this paper, we propose a liver segmentation algorithm using hybrid techniques by combining morphological-based, region-based and histogram-based techniques to segment volumetric CT data. A morphological-based technique is used to find the initial liver tissue from the first slice which is set as a starting slice and region-based is used for further processing for the rest slices, which incorporates seed point generation from Euclidean distance transform (EDT) image on the previous slice for region growing on the current slice. In order to remove neighboring abdominal organs of the liver which connect to the liver organ, the histogram-based technique is used by finding the left and right histogram tail threshold (HTT) and we repeat the use of morphology filtering and large contour detecting for liver smoothing.

关键词： Liver Computed tomography Computer aided diagnosis Image segmentation Euclidean distance Abdomen Histograms Tail Morphology Filtering

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Fuzzy Logic Based Algorithm for Disk Scheduling Policy

Fuzzy Logic Based Algorithm for Disk Scheduling Policy

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international conference of soft computing and pattern recognition (socpar)

作者： Mohamad Sofian Abu Talip Aisha Hassan Abdalla Ahmed Asif Abdurazzag Ali Aburas Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur Malaysia Faculty of Engineering and Natural Sciences International University of Sarajevo Sarajevo Bosnia and Herzegovina

Hard disk is the important component in computer system as data storage device. It is being used to store large amount of information in all modern computers. Disk performance can be improved by incorporating disk scheduling optimization for satisfy pending request in the disk queue. Operating system, being the interface between the user and the hardware, has the responsibility to use hardware efficiently. Current algorithm have not knowledge about the additional information provided by operating system and not been used for improvement of the seeking and/or tracking accessing. The paper present fuzzy model knowledge based for improving the disk scheduling. We use the Matlab implementation of this algorithm to compare and contrast the output with existing algorithms. Incorporating knowledge-based scheduling policy using fuzzy logic improves overall system behavior. The performance of the new disk scheduling algorithm based on fuzzy logic shows that the seek distance movement could be decreased by applying our methodology.

关键词： Fuzzy logic Scheduling algorithm Operating systems Magnetic heads Hardware Processor scheduling Hard disks Bandwidth Time measurement Control systems

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Temporal Speech Normalization Methods Comparison in Speech recognition Using Neural Network

Temporal Speech Normalization Methods Comparison in Speech R...

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international conference of soft computing and pattern recognition (socpar)

作者： Md Sah Bin Hj Salam Dzulkifli Mohamad Sheikh Hussain Shaikh Salleh Computer Science and Information System University Technology of Malaysia Skudai Johor Malaysia Bio-Med. and Health Science Engineering University Technology of Malaysia Skudai Johor Malaysia

Speech signal is temporally and acoustically varies. recognition of speech by static input neural network requires temporal normalization of the speech to be equal to the number of input nodes of the NN while maintaining the properties of the speech. This paper compares three methods for speech temporal normalization namely the linear, extended linear and zero padded normalizations on isolated speech using different sets of learning parameters on multi layer perceptron neural network with adaptive learning. Although, previous work shows that linear normalization able to give high accuracy up to 95% on similar problem, the result in this experiment shows the opposite. The experimental result shows that zero padded normalization outperformed the two linear normalization methods using all the parameter sets tested. The highest recognition rate using zero padded normalization is 99% while linear and extended linear normalizations give only 74% and 76% respectively. This paper end before conclusion by comparing data used from previous work using linear normalization which gave high accuracy and the data used in this experiment which perform poorer.

关键词： Speech recognition Neural networks pattern recognition Speech processing Speech analysis Adaptive systems Data mining Frequency Feature extraction Spectral analysis

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Telecommunication Fraud Prediction Using Backpropagation Neural Network

Telecommunication Fraud Prediction Using Backpropagation Neu...

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international conference of soft computing and pattern recognition (socpar)

作者： Azlinah Mohamed Ahmad Fuad Mohamed Bandi Abdul Razif Tamrin Md Daud Jaafar Suriah Hasan Faeizah Jusof Faculty of Computer & Mathematical Sciences Universiti Teknologi MARA Shah Alam Selangor Darul Ehsan Malaysia Telekom Research and Development Sdn. Bhd. TM Innovation Center Cyberjaya Malaysia

Telecommunication fraud prediction in this paper is an interpolation problem that uses the daily telecommunication network services information to analyze and predict the alarm information generated from a detection engine by minimizing false cases. This paper proposed the use of backpropagation neural network (BPNN) to perform telecommunication interpolation based on local telecommunication network services. The backpropagation algorithm is adjusted accordingly to control the speed of obtaining solution. The validation of this method is carried out following a series of experiments to establish the suitable BPNN parameters value for this interpolation problem. 20,000 cases were used and divided suitably into training and testing samples in analyzing the performance of the BPNN network. It is observed that the performance of BPNN in predicting fraud was merely 100% if the threshold value was set to 0.64 and above the predicted value. Consequently, the network model created could be used to analyze fraud risk classification and subsequently, provide contribution to the domain of fraud detection system.

关键词： Backpropagation Neural networks Design optimization Printing Integer linear programming Constraint optimization Testing Containers pattern recognition Computer applications

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Image Semantic Extraction Using Latent Semantic Indexing on Image Retrieval Automatic-Annotation

Image Semantic Extraction Using Latent Semantic Indexing on ...

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international conference of soft computing and pattern recognition (socpar)

作者： Yeni Herdiyeni Sri Nurdiati Imam Abu Daud Department of Computer Science Bogor Agricultural University Bogor Indonesia

This research proposed a new method Latent Semantic Indexing to overcome semantic problem on image retrieval based on automatic image annotation. Statistical machine translation used to automatically annotates the image. This approach considers image annotation as the translation of image regions to words, similar to the translation of text from one language to another. The "lexicon" for the translation is learned from large annotated image collections, which consist of images that are associated with text. Images are segmented into regions with grid segmentation. A pre-specified feature vector represents each region. The regions then clustered into a finite set of blobs. The correspondences between the blobs and the words are learned using Expectation Maximization algorithm. These correspondences are used to predict words associated with whole images (auto-annotation). The auto-annotation performance is evaluated using Normalized Score (E NS ) algorithm. The experimental results show that the average precision of clause queries achieved best result than word queries, 0.544 and 0.251 for clause queries and word queries respectively. The proposed method of latent semantic indexing succeeds to exploit semantic value of automatic-annotation-based image retrieval.

关键词： Indexing Image retrieval Design optimization Printing Integer linear programming Constraint optimization Testing Containers pattern recognition Computer applications

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Development of a Camera-Based Portable Automatic Inspection System for Printed Labels Using Neural Networks

引用

10th international Work-conference on Artificial Neural Networks (IWANN 2009)

作者： Shiraishi, Yuhki Takeda, Fumiaki Kochi Univ Technol Res Inst Kochi 7828502 Japan

ISBN: (纸本)9783642024801

For the automatic inspection for printed labels, which are covered with rubber-like coatings and Curl, we have developed a camera-based portable inspection system. In this paper, we explained the developed system, and especially discuss the inspection method of the spread and chip of the printed labels using neural networks. The experimental results confirm the validity of the proposed method for the spread and chip of alphanumerics.

关键词： Automatic optical inspection Image processing Image segmentation Machine vision Mechanical system pattern recognition Real time system

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Effects of the Use of Multiple Fuzzy Partitions on the Search Ability of Multiobjective Fuzzy Genetics-Based Machine Learning

Effects of the Use of Multiple Fuzzy Partitions on the Searc...

引用

international conference of soft computing and pattern recognition (socpar)

作者： Yusuke Nojima Yusuke Nakashima Hisao Ishibuchi Department of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University Sakai Osaka Japan

An important issue in the design of fuzzy rule-based systems is to find a good accuracy-complexity tradeoff. While simple fuzzy systems with high interpretability are usually not accurate, complicated fuzzy systems with high accuracy are usually not interpretable. Recently evolutionary multiobjective optimization (EMO) algorithms have been used to search for simple and accurate fuzzy systems. The main advantage of EMO-based approaches over single-objective techniques is that a number of alternative fuzzy systems with different accuracy-complexity tradeoffs can be obtained by their single run. We have already proposed a multiobjective fuzzy genetics-based machine learning (GBML) algorithm for pattern classification problems. In our GBML algorithm, multiple fuzzy partitions with different granularities are simultaneously used. This is because we usually do not know an appropriate fuzzy partition for each input variable. However, the use of multiple fuzzy partitions significantly increases the size of the search space. In this paper, we examine the effect of the use of multiple fuzzy partitions on the search ability of our multiobjective fuzzy GBML algorithms through computational experiments.

关键词： Machine learning Fuzzy systems Machine learning algorithms Partitioning algorithms Input variables Knowledge based systems Genetic algorithms Classification algorithms pattern classification Algorithm design and analysis

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A Hybrid Approach for Segmenting and Validating T1-Weighted Normal Brain MR Images by Employing ACM and ANN

A Hybrid Approach for Segmenting and Validating T1-Weighted ...

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international conference of soft computing and pattern recognition (socpar)

作者： M. Masroor Ahmed Dzulkifli Bin Mohamad Mohammad S. Khalil Faculty of Computer Science & Information System Universiti Teknologi Malaysia Skudai Skudai Malaysia

This study focuses on segmentation and validation of brain MR images. Artificial neural network (ANN) has been applied to obtain the targeted segments from these images. In preprocessing step for avoiding the chances of misclassification during training of ANN, the unwanted skull tissues were removed by employing active contour modeling (ACM). The removal of these tissues leaves an image containing various regions of interest. For training ANN these distinctive regions of interest were clustered into their respective regions by employing KMeans algorithm. Then a neural net work is trained on this classified data which eventually facilitated in obtaining the desired segments. The boundaries of these segments were detected and the pixels constituting these boundaries were counted. For validating the segments produced by ANN, ground truth segments were taken under consideration. The boundaries of these ground truth segments were also detected and pixels forming the edges of these segments were counted. Finally a comparison was drawn between the pixel counts of ANN produced segments and ground truth segments. On the basis of this comparison, accuracy of ANN is calculated.

关键词： Image segmentation Design optimization Printing Integer linear programming Constraint optimization Testing Containers pattern recognition Computer applications Laboratories

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