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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

共 1408 条记录，以下是581-590 订阅

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Simultaneous gene selection and cancer classification using a hybrid intelligent water drop approach

Simultaneous gene selection and cancer classification using ...

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5th international conference on pattern recognition and Machine Intelligence, PReMI 2013

作者： Kumar, Manish Ghosh, Shameek Valadi, Jayaraman Siarry, Patrick Bioinformatics Center University of Pune Pune India Centre for Development of Advanced Computing Pune India Shiv Nadar University Uttar Pradesh - 203207 India France

ISBN: (纸本)9783642450617

Computational Analysis of gene expression data is extremely difficult, due to the existence of a huge number of genes and less number of samples (limited number of patients). thus,it is of significant importance to provide a subset of the most informative genesto a learning algorithm, for constructing robust prediction models. In this study, we propose a hybrid Intelligent Water Drop (IWD) - Support Vector Machines (SVM) algorithm, with weighted gene ranking as a heuristic, for simultaneous gene subset selection and cancer prediction. Our results, evaluated on three cancer datasets, demonstrate that the genes selected by the IWD technique yield classification accuracies comparable to previously reported algorithms. © Springer-Verlag 2013.

关键词： Gene expression

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3D facial expression recognition on curvature local binary patterns

3D facial expression recognition on curvature local binary p...

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2013 5th international conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013

作者： Wang, Yiding Meng, Meng School of Information Engineering North China University of Technology Beijing China

ISBN: (纸本)9780769550114

this paper proposed a new method Based on curvature Based LBP feature to recognize 3D facial expression automatically. 3D facial expression images are described by means of four images which gray level are the value of curvature-Based descriptors (principal curvatures k1, k2, mean curvature, shape index) and then encoded by LBP. To efficiently optimize the performance, Chi-square distance is employed for classification. Finally, experimental result achieved on the Bosphorus database illustrates that the curvature-Based LBP (CLBP) has performs better than other features and also shows these features are significant for 3D facial expression recognition. © 2013 IEEE.

关键词： Local binary pattern

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A New Approach to Large-Scale Image recognition for Visual Search Engines

A New Approach to Large-Scale Image Recognition for Visual S...

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5th international Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

作者： Sezganov, Dmitry Porat, Moshe Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

ISBN: (纸本)9781479911776

Image and pattern recognition have become a significant task in recent years when most mobile communication devices have integrated cameras. the bag-of-words (BOW) approach is commonly used in information retrieval algorithms, and although originally developed for text, it has been adapted also for visual search. In spite of the similarity, there are different challenges - less effective weighting algorithms and quantization errors reduce the discrimination power of a single visual word. Moreover, the standard BOW algorithm completely ignores the geometric relationship between visual words. In this paper we introduce an efficient retrieval algorithm that accounts for geometric consistency constraints between two sets of local features that can be integrated with an inverted file. the algorithm significantly improves the initial ranking of the search results, promoting the more suitable candidates to the top of the results list. Application of the new algorithm shows that the proposed method outperforms presently available BOW retrieval algorithms even when followed by full geometric verification. Our conclusion is that the new algorithm and its associated data structure could be instrumental in improving image retrieval tasks.

关键词： Image Retrieval Computer Vision pattern recognition Scale-invariant Feature Transform (SIFT) Bag of Words (BOW)

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Study on Shaft Orbits Measurement and Identification Based on LabVIEW

Study on Shaft Orbits Measurement and Identification Based o...

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5th international conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Zhang Hongxin Zhou Hao Guo Xinping Meng Teng Hong Xinyu Yan Yu Harbin Univ Sci & Technol Sch Mech & Power Engn Harbin 150080 Heilongjiang Peoples R China

ISBN: (纸本)9780769549323

In order to measure and recognize shaft orbits a fault diagnosis system based on LabVIEW is developed. Integrating data acquisition, signal analysis and processing, information recognition and fault diagnosis, this system can automatically measure, analyze, identify the shaft orbits and get fault results. A pattern recognition method on the basis of the invariant moment algorithm is studied with LabVIEW and used to the shaft orbit recognition. the experimental results show that the shaft orbit of a rotor can be identified through this method and the shape is close to the ellipse. So the main fault of the rotor is imbalance. the fault result is verified by spectrum analysis. this study is helpful to develop the online fault diagnosis system based on LabVIEW.

关键词： Fault diagnosis Shaft orbits LabVIEW pattern recognition

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pattern recognition - 5th Mexican conference, MCPR 2013, Proceedings

Pattern Recognition - 5th Mexican Conference, MCPR 2013, Pro...

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5th Mexican conference on pattern recognition, MCPR 2013

ISBN: (纸本)9783642389887

the proceedings contain 38 papers. the topics discussed include: a fuzzy scheme for gait cycle phase detection oriented to medical diagnosis;virtual target formulation for singularity-free visual control using the trifocal tensor;assessing the quality level of corn tortillas with inductive characterization and digital image analysis;3D representation for object detection and verification;3D tracking and control of UAV using planar faces and monocular camera;third-eye stereo analysis evaluation enhanced by data measures;counting pedestrians in bidirectional scenarios using zenithal depth images;tracklet reidentification in crowded scenes using bag of spatio-temporal histograms of oriented gradients;LIDAR and panoramic camera extrinsic calibration approach using a pattern plane;video images fusion to improve iris recognition accuracy in unconstrained environments;and perception aptitude improvement of an odor sensor: model for a biologically inspired nose.

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Persian Handwritten Digits recognition by Using Zoning and Histogram Projection

Persian Handwritten Digits Recognition by Using Zoning and H...

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3rd Joint conference of AI and Robotics / 5th RoboCup Iran Open international Symposium

作者： Nooraliei, Amir Islamic Azad Univ Qazvin Branch Dept Elect Comp & IT Engn Qazvin Iran

ISBN: (纸本)9781467363150

In this paper, Persian handwritten digits reorganization by using zoning features and projection histogram for extracting feature vectors with 69-dimensions is presented. In classification stage, support vector machines (SVM) with three linear kernels, polynomial kernel and Gaussian kernel have been used as classifier. We tested our algorithm on the dataset that contained 8600 samples of Persian handwritten digits for performance analysis. Using 8000 samples in learning stage and another 600 samples in testing stage. the results got with use of every three kernels of support vector machine and achieved maximum accuracy by using Gaussian kernel with gamma equal to 0.16. In pre-processing stage only image binarization is used and all the images of this dataset had been normalized at center with size 40x40. the recognition rate of this method, on the test dataset 97.83% and on all samples of dataset 100% was earned.

关键词： pattern recognition Optical character recognition Support vector machine Persian handwritten digits

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Random weighting through linear programming into intracellular transporters of rice metabolic network

Random weighting through linear programming into intracellul...

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5th international conference on pattern recognition and Machine Intelligence, PReMI 2013

作者： Shaw, Rahul Kundu, Sudip Department of Biophysics Molecular Biology and Bioinformatics University of Calcutta Kolkata 700 009 India

ISBN: (纸本)9783642450617

An eukaryotic cell has different compartments which are specific to different biological activities. the total cellular metabolism is also compartmentalized. the intracellular transporters within a cell are responsible to transport some of the metabolites of one compartment to other. We formulate a model to understand the utility of different transporters. Here, we have taken a partially compartmentalized genome scale metabolic model of rice (Oryza sativa). Depending on the gene-expression, the transporters available to transport the metabolites from one compartment to other would change. We study the effect of transporter's capacity on the overall metabolism. We find that depending on the effectiveness of transporters, the photon demand for a rice leaf's biochemical machinery to synthesize the necessary biomass from inorganic nutrients, changes upto three fold. We also observe, interactions of mitochondrial and chloroplastid reactions are associated with this change. © Springer-Verlag 2013.

关键词： Linear programming

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An Efficient Character recognition Scheme Based on K-Means Clustering

An Efficient Character Recognition Scheme Based on K-Means C...

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5th international conference on Modeling, Simulation and Applied Optimization (ICMSAO)

作者： Pourmohammad, Sajjad Soosahabi, Reza Maida, Anthony S. Univ Louisiana Lafayette Ctr Adv Comp Studies Lafayette LA 70504 USA

ISBN: (纸本)9781467358149;9781467358125

Handwritten character recognition has been an active area of research. However, because of the recent advancements in mobile devices with limited amount of memory and computational power, efficient and simple algorithms for both online and offline character recognition have become more appealing. In this work, an efficient character recognition systems is proposed using LDA Analysis followed by a Bayesian discriminator function based on the Mahalonobis distance. Since LDA is tailored for Gaussian distributed data and the samples dimensionality is high, a couple of preprocessing steps have been applied to reduce dimensionality and cluster the data into semi-Gaussian subclasses. In the first step, affine transformations are applied to the training samples in order to make the scheme robust against distortion. Scaling and Rotation are among those popular distortions which have been considered in this work. Inactive pixels are cut off using a simple algorithm in the next step. then, principal component analysis (PCA) and k-means clustering are applied. the results from preprocessing showed a great potential in dimensionality reduction using transformations that can preserve useful information. Numerical results on the MNIST dataset reached 3% error rate which is lower than the other linear approaches. the proposed linear techniques are discussed in a way that make it easier to have a much clearer understanding of the method and why it works compared to the other classification methods.

关键词： Bayes methods Gaussian distribution affine transforms error statistics handwritten character recognition pattern clustering principal component analysis

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Learning semantic interaction among graspable objects

Learning semantic interaction among graspable objects

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5th international conference on pattern recognition and Machine Intelligence, PReMI 2013

作者： Panda, Swagatika Hafez, A. H. Abdul Jawahar, C.V. International Institute of Information Technology Hyderabad India

ISBN: (纸本)9783642450617

In this work, we aim at understanding semantic interaction among graspable objects in both direct and indirect physical contact for robotic manipulation tasks. Given an object of interest, its support relationship with other graspable objects is inferred hierarchically. the support relationship is used to predict the "support order" or the order in which the surrounding objects need to be removed in order to manipulate the target object. We believe, this can extend the scope of robotic manipulation tasks to typical clutter involving physical contact, overlap and objects of generic shapes and sizes. We have created an RGBD dataset consisting of various objects present in clutter using Kinect. We conducted our experimentation and analysed the performance of our work on the images from the same dataset. © Springer-Verlag 2013.

关键词： Robotics

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Built-in Smartphone Accelerometer Motion pattern recognition Using Wavelet Transform

Built-in Smartphone Accelerometer Motion Pattern Recognition...

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7th Int Conf on Soft Comp Models in Industrial and Environm Applications/5th Computational Intelligence in Security for Information Syst/3rd Int Conf on EUropean Transnational Educ

作者： Jirka, Jakub Prauzek, Michal Tech Univ Ostrava Dept Cybernet & Biomed Engn Ostrava Czech Republic

ISBN: (纸本)9783642330179

this paper is concerned with motion pattern recognition using built-in accelerometers inside of modern mobile devices - smartphones. More and more people are using these devices nowadays without using its full potential for user motion recognition and evaluation. As accelerometer magnitude level comparison is not sufficient for motion pattern recognition morlet wavelet based recognition algorithm is introduced and tested as well as its device implementation is described and tested. Set of basic motion patterns walking, running and shaking with the device is tested and evaluated.

关键词： Accelerometers

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