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"Influence areas" as a tool for testing of image restoration methods

"Influence areas" as a tool for testing of image restoration...

引用

2nd international conference on Applied Informatics and computing Theory, AICT'11

作者： Gribkov, Igor V. Koltsov, Peter P. Kotovich, Nikolay V. Kravchenko, Alexander A. Koutsaev, Alexander S. Osipov, Andrey S. Zakharov, Alexey V. Russian Academy of Sciences Scientific Research Institute for System Studies Department of Pattern Recognition and Videographic Information Processing Russia

ISBN: (纸本)9781618040343

In the paper we study energy methods for image restoration, when a restored image is obtained after minimization of an integral functional. Although such a functional is global, only few pixels in a small neighborhood of any pixel on the initial image can influence on the corresponding pixel on the restored image. We call this neighborhood an "influence area" and propose a technique for calculation of such areas and their visualization on computer screen. We apply the whole testing technique based upon this approach to a couple of known image restoration methods. The parameters of these methods, ensuring their better performance, are found.

关键词： Image reconstruction

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Dictionary Learning in Texture Classification 1

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8th international conference on Image Analysis and recognition (ICIAR) / 2nd international conference on Autonomous and Intelligent Systems (AIS)

作者： Gangeh, Mehrdad J. Ghodsi, Ali Kamel, Mohamed S. Univ Waterloo Dept Elect & Comp Engn Pattern Anal & Machine Intelligence PAMI Lab 200 Univ Ave W Waterloo ON N2L 3G1 Canada Univ Waterloo Dept Statist & Actuarial Sci Waterloo ON N2L 3G1 Canada

ISBN: (数字)9783642215933

ISBN: (纸本)9783642215926;9783642215933

Texture analysis is used in numerous applications in various fields. There have been many different approaches/techniques in the literature for texture analysis among which the texton-based approach that computes the primitive elements representing textures using k-means algorithm has shown great success. Recently, dictionary learning and sparse coding has provided state-of-the-art results in various applications. With recent advances in computing the dictionary and sparse coefficients using fast algorithms, it is possible to use these techniques to learn the primitive elements and histogram of them to represent textures. In this paper, online learning is used as fast implementation of sparse coding for texture classification. The results show similar to or better performance than texton based approach on CUReT database despite of computation of dictionary without taking into account the class labels.

关键词： Dictionary learning matrix factorization sparse coding texture classification

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Method of Laplacian Eigenmap-based pattern recognition and diagnosis for incipient fault of pipelines

Method of Laplacian Eigenmap-based pattern recognition and d...

引用

2011 international conference on Internet computing and Information Services, ICICIS 2011

作者： Lou, Zhigang Liu, Hongzhao Faculty of Mechanical and Precision Instrument Engineering Xi'an University of Technology Xi'an Shaanxi Province China

ISBN: (纸本)9780769545394

There is a considerable noise in the measured signal of pressure and flow of a running pipeline due to friction drag and medium diffusion, which poses an obstacle to the quick detection and precise classification of pipeline leakage, especially to the acquiring of weak incipient fault. This paper offers an incipient fault detection method based on nonlinear manifold learning algorithm, which treats the negative pressure wave signal as transient signal and reduces noise of original signal by using multi-scale wavelet transform. The method also learns original fault signal and extracts the intrinsic manifold features of data by using a nonlinear dimensionality reduction algorithm based on Laplacian Eigenmaps. With this method, the identification efficiency of optimal fault characteristics is noticeably improved, and the advantage of this method has been proved by simulation experiments. © 2011 IEEE.

关键词： Wavelet transforms

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An Innovative Positional pattern Detection Tool Applied to GAL4 Binding Sites in Yeast

An Innovative Positional Pattern Detection Tool Applied to G...

引用

international Joint conference on Neural Networks (IJCNN)

作者： Sichtig, Heike Riva, Alberto Univ Florida Dept Mol Genet & Microbiol Gainesville FL 32610 USA

ISBN: (纸本)9781424496365

The computational identification of regulatory elements in genomic DNA is key to understanding the regulatory infrastructure of a cell. We present an innovative tool to identify Transcription Factor Binding Sites (TFBSs) in genomic sequences. We show that our Positional pattern Detection tool is able to attain high sensitivity and specificity of TFBS detection by capturing dependencies between nucleotide positions within the TFBS, thereby elucidating complex interactions that may be critical for the TFBS activity. Further, we unveil a combination of two biologically realistic information processing methods that underlie our tool: third-generation neural networks (spiking neural networks) are used to represent the structure of TFBSs, and a genetic algorithm is used for optimization of network parameters. Initially, the networks are trained to distinguish known TFBS binding sites from negative examples in the learning phase. Then, the evolved network is used as a classifier to detect novel TFBSs in genomic sequences. Moreover, we show an application of our method to GAL4 binding sites in yeast. A two-neuron network topology is trained with real data from TRANSFAC and SCPD and evaluated through simulation. We show how neuron and synapse parameters can be evolved to improve classification results. Furthermore, the networks' predictions were compared against MAPPER, TFBIND and TFSEARCH. Our results reveal that our innovative tool has the potential to attain very high classification accuracy, with a very small number of false positives. These results show that information processing methods are able to capture important positional information in TFBSs and should be explored further to look at complex relationships underlying transcriptional and epigenetic regulation.

关键词： Biological cells Biological neural networks Delay GAL4 yeast binding site Genetic algorithms Neurons Pulse width modulation Training biology computing genetic algorithm genetic algorithms genomic DNA genomic sequence genomics learning (artificial intelligence) neural nets neural network training pattern recognition pattern recognition positional pattern detection tool spiking neural networks transcription factor binding sites

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The Final Sense Reverse Engineering Electroencephalography

The Final Sense Reverse Engineering Electroencephalography

引用

international conference on computing, Information and Control (ICCIC 2011)

作者： Aslam, Mohammed Zahid Visvesvaraya Technol Univ Alpha Coll Engn Bangalore Karnataka India

ISBN: (纸本)9783642240904

The human brain has the amazing ability to bombard itself with millions of bits of diverse information every day. It must also be able to store and convert these intelligent thoughts. In simpler terms, it does this by evaluating, sorting, figuring and redirecting information based on sequences and *** data being processed by the brain is already being studied by EEG (Electroencephalogram) at various levels of research and for clinical purposes. This paper introduces the idea of reverse engineering the concept used in EEG's and "write" data into the brain. This device will apply the required voltage in micro volts to the different parts of the brain externally using EEG electrodes. Thus instead of the basic senses converting physical images and characters, sounds etc into certain voltages being transmitted to the brain, an external device (such as an EEG) can convey the information to the brain.

关键词： Brain Electroencephalography Medical treatment pattern recognition stochastic automata

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引用

2nd international conference on Ubiquitous computing and Multimedia Applications

作者： Bhattacharyya, Debnath Kim, Tai-hoon Hannam Univ Dept Multimedia Daejeon South Korea MPCT Dept Comp Sci & Engn Gwalior India

ISBN: (纸本)9783642209970

In this paper we propose a statistical similarity checking method to identify the similarity between two handwritten signatures. Initially, we process the handwritten signature images in various image processing techniques and store in a magnetic storage device. In turn, during the time of similarity checking, our algorithm generates a binary dotplot matrix for each of the signature image in the storage with the input signature image of a particular user domain. In this paper, these binary dotplot matrices guide us to identify the degree of similarity or homology or duplicate copy of handwritten signature of any user. In this paper we deal with only binary dotplot similarity technique.

关键词： pattern recognition bio-informatics similarity Image processing binary dotplot

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Time Series pattern recognition via softcomputing

Time Series Pattern Recognition via SoftComputing

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international conference on P2P, Parallel, Grid, Cloud and Internet computing (3PGCIC)

作者： Martin Kotyrba Zuzana Oplatkova Eva Volna Roman Senkerik Vaclav Kocian Michal Janosek Department of Informatics and Computers University of Ostrava Ostrava Czech Republic Faculty of Applied Informatics Tomas Bata University Zlin Zlin Czech Republic

In this paper we develop two methods that are able to analyze and recognize patterns in time series. The first model is based on analytic programming (AP), which belongs to soft computing. AP is based as well as genetic programming on the set of functions, operators and so-called terminals, which are usually constants or independent variables. The second one uses an artificial neural network that is adapted by back propagation. Artificial neural networks are suitable for pattern recognition in time series mainly because of learning only from examples. There is no need to add additional information that could bring more confusion than recognition effect. Neural networks are able to generalize and are resistant to noise. On the other hand, it is generally not possible to determine exactly what a neural network learned and it is also hard to estimate possible recognition error. They are ideal especially when we do not have any other description of the observed series. This paper also includes experimental results of time series pattern recognition carried out with both mentioned methods, which have proven their suitability for this type of problem solving.

关键词： Neurons Time series analysis Programming pattern recognition Training Biological neural networks Vectors

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Age Regression from soft Aligned Face Images Using Low Computational Resources

引用

5th Iberian conference on pattern recognition and Image Analysis (IbPRIA)

作者： Bekios-Calfa, Juan Buenaposada, Jose M. Baumela, Luis Univ Catolica Norte Dept Ingn Sistemas & Computac Av Angamos 0610 Antofagasta Chile Univ Rey Juan Carlos Dept Ciencias Computac Mostoles Spain Univ Politecn Madrid Dept Artificial Intelligence Madrid Spain

ISBN: (纸本)9783642212567;9783642212574

The initial step in most facial age estimation systems consists of accurately aligning a model to the output of a face detector (e. g. an Active Appearance Model). This fitting process is very expensive in terms of computational resources and prone to get stuck in local minima. This makes it impractical for analysing faces in resource limited computing devices. In this paper we build a face age regressor that is able to work directly on faces cropped using a state-of-the-art face detector. Our procedure uses K nearest neighbours (K-NN) regression with a metric based on a properly tuned Fisher Linear Discriminant Analysis (LDA) projection matrix. On FG-NET we achieve a state-of-the-art Mean Absolute Error (MAE) of 5.72 years with manually aligned faces. Using face images cropped by a face detector we get a MAE of 6.87 years in the same database. Moreover, most of the algorithms presented in the literature have been evaluated on single database experiments and therefore, they report optimistically biased results. In our cross-database experiments we get a MAE of roughly 12 years, which would be the expected performance in a real world application.

关键词： Database systems

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Affective computing and Intelligent Interaction - 4th international conference, ACII 2011, Proceedings

Affective Computing and Intelligent Interaction - 4th Intern...

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4th international conference on Affective computing and Intelligent Interaction, ACII 2011

ISBN: (纸本)9783642245992

The proceedings contain 130 papers. The topics discussed include: affective modeling from multichannel physiology: analysis of day differences;the dynamics between student affect and behavior occurring outside of educational software;unsupervised temporal segmentation of talking faces using visual cues to improve emotion recognition;the affective experience of handling digital fabrics: tactile and visual cross-modal effects;predicting learner engagement during well-defined and ill-defined computer-based intercultural interactions;a pattern-based model for generating text to express emotion;interpretations of artificial subtle expressions (ASEs) in terms of different types of artifact: a comparison of an on-screen artifact with a robot;relevance vector machine based speech emotion recognition;toward a computational model of affective responses to stories for augmenting narrative generation;and toward a computational model of affective responses to stories for augmenting narrative generation.

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Affective computing and Intelligent Interaction - 4th international conference, ACII 2011, Proceedings

Affective Computing and Intelligent Interaction - 4th Intern...

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4th international conference on Affective computing and Intelligent Interaction, ACII 2011

ISBN: (纸本)9783642245701

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