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pattern recognition methods for SAW sensor array based electronic nose

Pattern recognition methods for SAW sensor array based elect...

引用

IEEE international conference on Computational Intelligence and computing Research

作者： S. K. Jha R. D. S. Yadava Department of Physics Faculty of Science Banaras Hindu University Varanasi India

The paper presents an analysis of several preprocessing, feature extraction and classification methods in combination for yielding optimum performance for SAW sensors array based electronic nose systems. It is found that the combination of logarithmic data preprocessing, linear discriminant analysis based feature extraction and support vector machine based classification yields optimum results.

关键词： Feature extraction Arrays Surface acoustic waves Support vector machines Principal component analysis pattern recognition Artificial neural networks

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A model to classify the disease pattern based on similarity degree method

A model to classify the disease pattern based on similarity ...

引用

IEEE international conference on Intelligent computing and Intelligent Systems (ICIS)

作者： Wenxue Tan Xiping Wang Jinju Xi Yutong Bi College of Computer Science and Technology Hunan University of Arts and Sciences Changde China College of Computer Science and Technology Hunan University of Arts and Science Changde China College of Economy and Management Hunan University of Arts and Science Changde China College of Economy and Management Hunan University of Arts and Sciences Changde China

In order to help human expert resolve the problem of diagnosing disease, we analyze the comparability and relativity between pattern recognition and disease diagnosis in terms of the solution means, and propose the theoretical model of disease-similarity-degree pattern recognition on the basis of certainty factors vectors and fuzzy membership factors vectors, and its corresponding data structure mode. In addition, the software hierarchy of model and recognition algorithm, and its practice method are designed. Field experiment statistics demonstrate that: compared with the individual human expert, the proposed model be able to obtain a favorable accuracy rate of diagnosis over 85%, and reduce a rate of misdiagnosis effectively, which provided with a preferential comprehensive diagnosis performance.

关键词： Industries

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Integrate and Fire neurons and their application in pattern recognition

Integrate and Fire neurons and their application in pattern ...

引用

international conference on Electrical Engineering, computing Science and Automatic Control (CCE)

作者： Roberto A. Vazquez Aleister Cachón Escuela de Ingeniería Universidad de La Salle Mexico Mexico Escuela de Ingeniería Universidad La Salle México D.F. México

In this paper, it is shown how a Leaky Integrate and Fire (LIF) neuron can be applied to solve non-linear pattern recognition problems. Given a set of input patterns belonging to K classes, each input pattern is transformed into an input signal, then the LIF neuron is stimulated during T ms and finally the firing rate is computed. After adjusting the synaptic weights of the neuron model, we expect that input patterns belonging to the same class generate almost the same firing rate and input patterns belonging to different classes generate firing rates different enough to discriminate among the different classes. At last, a comparison between a feed-forward neural network and the LIF neuron is presented when applied to solve non-linear problems.

关键词： Neurons Artificial neural networks Firing Computational modeling pattern recognition Classification algorithms Accuracy

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computing the Barycenter Graph by Means of the Graph Edit Distance

Computing the Barycenter Graph by Means of the Graph Edit Di...

引用

international conference on pattern recognition

作者： Itziar Bardaji Miquel Ferrer Alberto Sanfeliu Institut de Robòtica in Informàtica Industrial UPC-CSIC Spain

ISBN: (纸本)9781424475421

The barycenter graph has been shown as an alternative to obtain the representative of a given set of graphs. In this paper we propose an extension of the original algorithm which makes use of the graph edit distance in conjunction with the weighted mean of a pair of graphs. Our main contribution is that we can apply the method to attributed graphs with any kind of labels in both the nodes and the edges, equipped with a distance function less constrained than in previous approaches. Experiments done on four different datasets support the validity of the method giving good approximations of the barycenter graph.

关键词： Databases Approximation algorithms Approximation methods Sorting pattern recognition Upper bound Entropy

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13th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI)

作者： Sorensen, Lauge Loog, Marco Lo, Pechin Ashraf, Haseem Dirksen, Asger Duin, Robert P. W. de Bruijne, Marleen Univ Copenhagen Dept Comp Sci Image Grp DK-1168 Copenhagen Denmark Gentofte Univ Hosp Dept Med Res Gentofte Denmark Dept Radiol & Med Biomedo Imaging Grp Rotterdam Erasmus MC Netherlands Delft Univ Technol Pattern Recognition Lab Delft Netherlands

ISBN: (纸本)9783642157042

In this paper, we propose to classify medical images using dissimilarities computed between collections of regions of interest. The images are mapped into a dissimilarity space using an image dissimilarity measure, and a standard vector space-based classifier is applied in this space. The classification output of this approach can be used in computer aided-diagnosis problems where the goal is to detect the presence of abnormal regions or to quantify the extent or severity of abnormalities in these regions. The proposed approach is applied to quantify chronic obstructive pulmonary disease in computed tomography (CT) images, achieving an area under the receiver operating characteristic curve of 0.817. This is significantly better compared to combining individual region classifications into an overall image classification, and compared to common computerized quantitative measures in pulmonary CT.

关键词： Computer aided diagnosis

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Transition Thresholds for Binarization of Historical Documents

Transition Thresholds for Binarization of Historical Documen...

引用

international conference on pattern recognition

作者： Marte A. Ramírez-Ortegon Raul Rojas Institut für Informatik Freie Universität Berlin Berlin Germany

This paper extends the transition method for binarization based on transition pixels, a generalization of edge pixels. This method originally computes transition thresholds using the quantile thresholding algorithm, that has a critical parameter. We achieved an automatic version of the transition method by computing the transition thresholds with the Rosin's algorithm. We experimentally tested four variants of the transition method combining the density and cumulative distribution functions of transition values, with gray-intensity thresholds based on the normal and lognormal density functions. The results of our experiments show that these unsupervised methods yields superior binarization compared with top-ranked algorithms.

关键词： Pixel Histograms Optical character recognition software pattern recognition Approximation methods Algorithm design and analysis Density functional theory

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Lower and Upper Rough Submodules

Lower and Upper Rough Submodules

引用

international conference on computing Control and Industrial Engineering (CCIE)

作者： Gang Fang School of Computer Science Guangdong Polytechnic Normal University Guangzhou China

ISBN: (纸本)9781424467501;9780769540269

In recent several years, the rough set theory has been rapidly developed and applied in pattern recognition, machinery study, decision-making analysis and supporting. The theory of rough sets deals with the approximation of an arbitrary subset of a universe by two definable or observable subsets called lower and upper approximation. In this paper, we shall extend rough sets to module theory by introducing the notions of so called lower and upper rough submodules in a R-module, and give two main results as follows: If A and B are upper rough θ w -submodules of M, then A+B is an upper rough θ w -submodule of M; If A and B are lower rough θ w -submodules of M, then A∩B is an lower rough θ w -submodule of M.

关键词： Rough sets Industrial engineering Computer science Set theory pattern recognition Machinery Decision making pattern analysis Algebra Mathematics

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On the Fusion of Periocular and Iris Biometrics in Non-ideal Imagery

On the Fusion of Periocular and Iris Biometrics in Non-ideal...

引用

international conference on pattern recognition

作者： Damon L. Woodard Shrinivas Pundlik Philip Miller Raghavender Jillela Arun Ross Biometrics and Pattern Recognition Laboratory School of Computing Clemson University USA Lane Department of Computer Science and Electrical Engineering West Virginia University USA

Human recognition based on the iris biometric is severely impacted when encountering non-ideal images of the eye characterized by occluded irises, motion and spatial blur, poor contrast, and illumination artifacts. This paper discusses the use of the periocular region surrounding the iris, along with the iris texture patterns, in order to improve the overall recognition performance in such images. Periocular texture is extracted from a small, fixed region of the skin surrounding the eye. Experiments on the images extracted from the Near Infra-Red (NIR) face videos of the Multi Biometric Grand Challenge (MBGC) dataset demonstrate that valuable information is contained in the periocular region and it can be fused with the iris texture to improve the overall identification accuracy in non-ideal situations.

关键词： Iris recognition Videos Pixel Skin Databases Face recognition

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pattern recognition Method Using Ensembles of Regularities Found by Optimal Partitioning

Pattern Recognition Method Using Ensembles of Regularities F...

引用

international conference on pattern recognition

作者： Oleg V. Senko Anna V. Kuznetsova Dorodnicyn Computing Centre Russian Academy of Science Moscow Russia Emanuel Institute of Biochemical Physics Russian Academy of Science Moscow Russia

ISBN: (纸本)9781424475421

New pattern recognition method is considered that is based on ensembles of ”syndromes”. The developed method that is referred to as Multi-model statistically weighted syndromes (MSWS) is further development of earlier Statistically Weighted Syndromes (SWS) method. ”Syndromes” are subregions in space of prognostic features where content of objects from one of the classes differs significantly from the same class contents in neighboring subregions. ”Syndromes” are discussed as simple basic classifiers that are combined with the help of weighted voting procedure. Method of optimal partitioning of input features space is used for ”syndromes” searching. At that ”syndromes” are selected depending on quality of data separation and complexity of used partitioning model (partitions family). Performance of MSWS is compared with performance of SWS and alternative techniques in several applied tasks. Influence of recognition ability on characteristics of ”syndromes” selection is studied.

关键词： Accuracy pattern recognition Support vector machines Training Cancer Artificial neural networks Forecasting

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A New Symmetry Based on Proximity of Wavelet-Moments for Text Frame Classification in Video

A New Symmetry Based on Proximity of Wavelet-Moments for Tex...

引用

international conference on pattern recognition

作者： Palaiahnakote Shivakumara Anjan Dutta Chew Lim Tan Umapada Pal School of Computing National University of Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

This paper proposes the use of a new symmetry property based on proximity of the median moments in the wavelet domain. The method divides a given frame into 16 equally sized blocks to classify the true text frame. The average of high frequency subbands of a block is used for computing median moments to brighten the text pixel in a block of video frame. Then K-means clustering with K=2 is applied on the median moments of the block to classify it as a probable text block. For classified blocks, average wavelet median moments are computed for a sliding window. We introduce Max-Min cluster to classify the probable text pixel in each probable text block. The four quadrants are formed from the centroid of the probable text pixels. The new concept called symmetry is introduced to identify the true text block based on proximity between probable text pixels in each quadrant. If the frame produces at least one true text block, it is considered as a text frame otherwise a non-text frame. The method is tested on three datasets to evaluate the robustness of the method in classification of text frames in terms of recall and precision.

关键词： Pixel Chromium Feature extraction pattern recognition Robustness Silicon Classification algorithms

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