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2009 Journal article Restricted

A heavy-tailed empirical Bayes method for replicated microarray data
Salas-gonzalez D., Kuruoglu E. E., Ruiz D. P.
DNAmicroarray has been recognized as being an important tool for studying the expression of thousands of genes simultaneously. These experiments allow us to compare two different samples of cDNA obtained under different conditions. A novel method for the analysis of replicated microarray experiments based upon the modelling of gene expression distribution as a mixture of alpha-stable distributions is presented. Some features of the distribution of gene expression, such as Pareto tails and the fact that the variance of any given array increases concomitantly with an increase in the number of genes studied, suggest the possibility of modelling gene expression distribution on the basis of alpha-stable density. The proposed methodology uses very well known properties of alpha-stable distribution, such as the scale mixture of normals. A Bayesian log-posterior odds is calculated, which allows us to decide whether a gene is expressed differentially or not. The proposed methodology is illustrated using simulated and experimental data and the results are compared with other existing statistical approaches. The proposed heavy-tail model improves the performance of other distributions and is easily applicable to microarray gene data, specially if the dataset contains outliers or presents high variance between replicates.Source: Computational statistics & data analysis (Print) 53 (2009): 1535–1546. doi:10.1016/j.csda.2008.08.008
DOI: 10.1016/j.csda.2008.08.008

See at: Computational Statistics & Data Analysis Restricted | Computational Statistics & Data Analysis Restricted | Computational Statistics & Data Analysis Restricted | Computational Statistics & Data Analysis Restricted | Computational Statistics & Data Analysis Restricted | Computational Statistics & Data Analysis Restricted | CNR ExploRA Restricted | Computational Statistics & Data Analysis Restricted | www.sciencedirect.com Restricted


2009 Journal article Restricted

Astrophysical image separation by blind time-frequency source separation methods
Ozgen M. T., Kuruoglu E. E., Herranz D.
In this paper, two prevalent blind time-frequency (TF) source separation methods in the literature are adapted to astrophysical image mixtures and four algorithms are developed to separate them into their astrophysical components. The components considered in this work are cosmic microwave background (CMB) radiation, galactic dust and synchrotron, among which the CMB component is emphasized. These simulated components mixed via realistic coefficients are subjected to simulated additive, nonstationary Gaussian noise components of realistic power levels, to yield image mixtures on which our orthogonal and nonorthogonal TF algorithms are applied. The developed algorithms are compared with the FastICA algorithm and CMB component is found to be recovered with an improvement reaching to 3.25 decibels from CMB-synchrotron mixtures. The proposed techniques are believed to be generically applicable in separating other types of astrophysical components as well.Source: Digital signal processing (Print) 19 (2009): 360–369. doi:10.1016/j.dsp.2007.12.003
DOI: 10.1016/j.dsp.2007.12.003

See at: Digital Signal Processing Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | CNR ExploRA Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | www.sciencedirect.com Restricted


2009 Journal article Restricted

Bayesian separation of images modelled with MRFs using MCMC
Kayabol K., Kuruoglu E. E., Sankur B.
We investigate the source separation problem of random fields within a Bayesian framework. The Bayesian formulation enables the incorporation of prior image models in the estimation of sources. Due to the intractability of the analytical solution we resort to numerical methods for the joint maximization of the a posteriori distribution of the unknown variables and parameters. We construct the prior densities of pixels using Markov random fields based on a statistical model of the gradient image, and we use a fully Bayesian method with modified-Gibbs sampling. We contrast our work to approximate Bayesian solutions such as Iterated Conditional Modes (ICM) and to non-Bayesian solutions of ICA variety. The performance of the method is tested on synthetic mixtures of texture images and astrophysical images under various noise scenarios. The proposed method is shown to outperform significantly both its approximate Bayesian and non-Bayesian competitors.Source: IEEE transactions on image processing 18 (2009): 982–994. doi:10.1109/TIP.2009.2012905
DOI: 10.1109/tip.2009.2012905

See at: IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted


2009 Journal article Restricted

Finite mixture of alpha-stable distributions
Salas-gonzalez D., Kuruoglu E. E., Ruiz D. P.
Over the last decades, the ±-stable distribution has proved to be a very efficient model for impulsive data. In this paper, we propose an extension of stable distributions, namely mixture of ±-stable distributions to model multimodal, skewed and impulsive data. A fully Bayesian framework is presented for the estimation of the stable density parameters and the mixture parameters. As opposed to most previous work on mixture models, the model order is assumed unknown and is estimated using reversible jump Markov chain Monte Carlo. It is important to note that the Gaussian mixture model is a special case of the presented model which provides additional flexibility to model skewed and impulsive phenomena. The algorithm is tested using synthetic and real data, accurately estimating ±-stable parameters, mixture coefficients and the number of components in the mixture.Source: Digital signal processing (Print) 19 (2009): 250–264. doi:10.1016/j.dsp.2007.11.004
DOI: 10.1016/j.dsp.2007.11.004

See at: Digital Signal Processing Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted | CNR ExploRA Restricted | Digital Signal Processing Restricted | Digital Signal Processing Restricted


2009 Conference article Restricted

ICA by maximizing non-stability
Wang B., Kuruoglu E. E., Zhang J.
We propose a new approach for ICA by maximizing the non-stability contrast function in this paper. This new version of ICA is motivated by the Generalized Central Limit Theorem (GCLT), an important extension of classical CLT. We demonstrate that the classical ICA based on maximization of non-Gaussianity is a special case of the new approach of ICA we introduce here which is based on maximization of non-Stability with certain constraints. To be able to quantify non-stability, we introduce a new measure of stability namely Alpha-stable negentropy. A numerical gradient ascent algorithm for the maximization of the alpha-stable negentropy with the objective of source separation is also introduced in this paper. Experiments show that ICA by maximum of non-stability performs very successfully in impulsive source separation problems.Source: Independent Component Analysis and Signal Separation. 8th International Conference, pp. 179–186, Paraty, Rio Janerio, Brasile, 15-18 Marzo 2009
DOI: 10.1007/978-3-642-00599-2_23

See at: academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | dl.acm.org Restricted | doi.org Restricted | link.springer.com Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2009 Conference article Open Access OPEN

Image source separation using color channel dependencies
Kayabol K., Kuruoglu E. E., Sankur B.
We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of color images which have dependence between its components. A Markov Random Field (MRF) is used for modeling of the inter and intra-source local correlations. We resort to Gibbs sampling algorithm for obtaining the MAP estimate of the sources since non-Gaussian priors are adopted. We test the performance of the proposed method both on synthetic color texture mixtures and a realistic color scene captured with a spurious reflection.Source: Independent Component Analysis and Signal Separation. 8th International Conference, pp. 499–506, Paraty, Brazil, 15-18 March 2009
DOI: 10.1007/978-3-642-00599-2_63

See at: Aperta TÜBİTAK Open Archive Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | dl.acm.org Restricted | link.springer.com Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2009 Journal article Open Access OPEN

Modelling and assessing differential gene expression using the alpha stable distribution
Salas-gonzalez D., Kuruoglu E. E., Ruiz D. P.
After normalization, the distribution of gene expressions for very different organisms have a similar shape, usually exhibit heavier tails than a Gaussian distribution, and have a certain degree of asymmetry. Therefore, this distribution has been modeled in the literature using different parametric families of distributions, such the Asymmetric Laplace or the Cauchy distribution. Moreover, it is known that the tails of spot-intensity distributions are described by a power law and the variance of a given array increases with the number of genes. These features of the distribution of gene expression strongly suggest that the alpha-stable distribution is suitable to model it. In this work, we model the error distribution for gene expression data using the alpha-stable distribution. This distribution is tested successfully for four different datasets. The Kullback-Leibler, Chi-square and Hellinger tests are performed to compare how alpha-stable, Asymmetric Laplace and Gaussian fit the spot intensity distribution. The alpha-stable is proved to perform much better for every array in every dataset considered. Furthermore, using an alpha-stable mixture model, a Bayesian log-posterior odds is calculated allowing us to decide whether a gene is differently expressed or not. This statistic is based on the Scale Mixture of Normals and other well known properties of the alpha-stable distribution. The proposed methodology is illustrated using simulated data and the results are compared with the other existing statistical approach.Source: The international journal of biostatistics 5 (2009): 16–24. doi:10.2202/1557-4679.1120
DOI: 10.2202/1557-4679.1120

See at: CNR ExploRA Open Access | www.bepress.com Open Access | The International Journal of Biostatistics Open Access | The International Journal of Biostatistics Restricted | The International Journal of Biostatistics Restricted | The International Journal of Biostatistics Restricted | The International Journal of Biostatistics Restricted | The International Journal of Biostatistics Restricted | The International Journal of Biostatistics Restricted


2009 Journal article Restricted

Permittivity range profile reconstruction of multilayered structures from microwave backscattering data by using particle swarm optimization
Genovesi S., Salerno E., Monorchio A., Manara G.
A method for the investigation of multilayered structures by using microwave probes is proposed. An iterative optimization procedure reconstructs the permittivity range profiles of such structures from backscattering data by optimizing a functional with a data term and a regularization term, including a line process to overcome the global smoothness enforced by classical regularization.Source: Microwave and optical technology letters (Print) 51 (2009): 2390–2394. doi:10.1002/mop.24642
DOI: 10.1002/mop.24642

See at: Microwave and Optical Technology Letters Restricted | Microwave and Optical Technology Letters Restricted | Microwave and Optical Technology Letters Restricted | Microwave and Optical Technology Letters Restricted | Microwave and Optical Technology Letters Restricted | onlinelibrary.wiley.com Restricted | Microwave and Optical Technology Letters Restricted | CNR ExploRA Restricted


2009 Journal article Unknown

Diagnosis of lymphatic tumors by case-based reasoning on microscopic images
Colantonio S., Perner P., Salvetti O.
In this paper, a novel method for diagnosing lymphatic tissue tumors is presented. Microscopic specimen images are analyzed for extracting and characterizing malignant cells. A case-based reasoning approach is followed for classifying morphologic and densitometric cell features so as to provide a final diagnosis.Source: 2 (2009): 29–40.

See at: CNR ExploRA


2009 Journal article Restricted

An ontological framework for media analysis and mining
Colantonio S., Salvetti O., Gurevich I. B., Trusova Y.
Advances in tools and technologies for digital media production and analysis have assured the availability of larger and larger amount of data which carry a huge amount of information for solving specific application tasks. This development has stressed the need for advanced systems that are not limited to media storage and management but include also their intelligent representation and retrieval. In this paper, we report current results of an ontological framework under development for mining media data, thus offering the possibility of storing, retrieving, analyzing and investigating media to discover novel knowledge relevant to strategic application processes.Source: Pattern recognition and image analysis 19 (2009): 221–230. doi:10.1134/S1054661809020023
DOI: 10.1134/s1054661809020023

See at: Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | CNR ExploRA Restricted


2009 Journal article Restricted

Heart deformation pattern analysis through shape modelling
Moroni D., Colantonio S., Salvetti O., Salvetti M.
In this paper, we present an approach to the description of time-varying anatomical structures. The main goal is to compactly but faithfully describe the whole heart cycle in such a way to allow for deformation pattern characterization and assessment. Using such an encoding, a reference database can be built, thus permitting similarity searches or data mining procedures.Source: Pattern recognition and image analysis 19 (2009): 262–270. doi:10.1134/S1054661809020084
DOI: 10.1134/s1054661809020084

See at: Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | link.springer.com Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | CNR ExploRA Restricted


2009 Journal article Restricted

Il Web semantico
Martinelli M.
Interview on Semantic WebSource: Internet magazine (Lond.) 135 F (2009): 82–83.

See at: CNR ExploRA Restricted


2009 Journal article Restricted

Object tracking in video-surveillance
Moroni D., Pieri G.
This paper faces the automatic object tracking problem in a video-surveillance task. A previously selected and then identified target has to be retrieved in the scene under investigation because it is lost due to masking, occlusions, or quick and unexpected movements. A two-step procedure is used, firstly motion detection is used to determine a candidate target in the scene, secondly using a semantic categorization and Content Based Image Retrieval techniques, the candidate target is identified whether it is the one that was lost or not. The use of Content Based Image Retrieval serves as support to the search problem and is performed using a reference data base which was populated a priori.Source: Pattern recognition and image analysis 19 (2009): 271–276. doi:10.1134/S1054661809020096
DOI: 10.1134/s1054661809020096

See at: Pattern Recognition and Image Analysis Restricted | link.springer.com Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | CNR ExploRA Restricted


2009 Conference article Restricted

Ontology-based framework to image mining
Colantonio S., Gurevich I. B., Pieri G., Salvetti O., Trusova Y.
A novel knowledge-based approach for supporting image processing and analysis is presented as well as its use within a framework for image mining. Modern approaches to knowledge representation, ontologies and reasoning, have been combined with techniques for image processing, analysis and understanding within a semantic framework able to support the extraction of novel knowledge for image collectionsSource: 2nd International Workshop on Image Mining Theory and Applications, pp. 11–19, Lisboa, Portugal, 7-8 February 2009

See at: CNR ExploRA Restricted


2009 Conference article Restricted

A decision support system for aiding heart failure management
Colantonio S., Martinelli M., Moroni D., Salvetti O., Chiarugi F., Emmanouilidou D.
The purpose of this paper is to present an effective way to achieve a high-level integration of a Clinical Decision Support System in the general process of Heart Failure care and to discuss the advantages of such an approach. In particular, the relevant and significant medical knowledge and experts' know-how have been modelled according to an ontological formalism extended with a base of rules for inferential reasoning. These have been also combined with advanced analytical tools for data processing. In particular, methods for the segmentation of echocardiographic image sequences and algorithms for ECG processing have been implemented and integrated into the system.Source: Ninth International Conference on Intelligent Systems Design and Applications, pp. 351–356, Pisa, 30 NOvember -2 December 2009
DOI: 10.1109/isda.2009.117

See at: academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | doi.ieeecomputersociety.org Restricted | ieeexplore.ieee.org Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | www.microsoft.com Restricted | xplorestaging.ieee.org Restricted | yadda.icm.edu.pl Restricted


2009 Conference article Restricted

Astrophysical component separation with Langevin sampler
Kayabol K., Kuruoglu E. E., Sankur B.
Lighting artifacts are one of the main issues in digital photography: complex light setups are needed to attenuate or remove them. Flash light is a very easy way to illuminate an object or an environment, but it is rarely considered in most of the Computer Graphics and Computer Vision applications. This is due to the big amount of artifacts introduced by this lighting, and to the difficulty in modeling its behavior. In this paper we present a simple method to use flash light in the context of color acquisition and mapping on 3D models. We propose a simple way to accurately estimate the flash position with respect to the camera, and we propose two automatic methods to detect and remove artifacts from a set of images which are registered to a 3D model. These methods are integrated in the context of a color mapping framework. The results show that it is possible to obtain high quality colored 3D models using flash light, which is the most simple illumination setup. This results are extremely important especially in the context of Cultural heritage, where the acquisition of color has often to be performed on site, without a specific lighting setup.Source: IEEE 17th Signal Processing and Communications Applications Conference, pp. 77–84, Antalya/Turkey, 9-11 April 2009
DOI: 10.1109/siu.2009.5136378

See at: academic.microsoft.com Restricted | ieeexplore.ieee.org Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | xplorestaging.ieee.org Restricted | yadda.icm.edu.pl Restricted


2009 Contribution to conference Unknown

Brass instrument making in Milan: 1800 - 1850
Carreras F., Meroni C.
Source: Romantic Brass Symposium, Berna, 2009

See at: CNR ExploRA


2009 Contribution to conference Open Access OPEN

Un dispositivo portatile basato su DSP per un migliore ascolto della musica in soggetti ipoacusici
Bertini G., Massimo M., Paolini F.
Source: DSP Application Day 2009 e-Conference & Webinar, Milano, 2009

See at: ISTI Repository Open Access | CNR ExploRA


2009 Contribution to conference Open Access OPEN

Extracting erased text from palimpsests by using visible light
Salerno E., Tonazzini A.
Recently, high resolution specialized imaging has been giving a substantial help in reading palimpsested manuscripts without using invasive practices, often harmful for historically important ancient documents. In particular, faint traces of the erased texts can be highlighted by ultraviolet illumination (Wood lamps). By image processing techniques, the fluorescence images thus obtained can complement the reflection or transmission images under visible-light illumination to further help the scholar in distinguishing the erased text from the overwriting. Fluorescence images are not always available to be processed. In some cases, however, we have observed that a suitable processing of the standard color channels can help in distinguishing the two texts even though no additional channel is available. In general, different inks show different spectral signatures, thus the two texts to be distinguished may tend to fade over different wavelength ranges. This is how multispectral or hyperspectral imaging using both reflection and fluorescence, and covering the visible plus some of the infrared and ultraviolet bands, can enable us to separate the texts. Indeed, by inspecting the channel images, one can find some wavelength range where one of the two texts disappears, whereas the other has still a good contrast. By exploiting this feature, a pseudocolor image can be built, where one of the two texts is perceptually well separated from the other (e.g. it might appear in a totally different color). Any human observer would now be capable to decorrelate the two text patterns with no further mathematical image processing. If a standard color image is only available, both patterns are normally visible in all the channels, and the strategy described above cannot be applied so straightforwardly. However, spectral diversity can still be exploited to improve the readability of the underwritten text through a pseudocolor image that can be very similar to the one obtained by using a fluorescence channel. The key to the procedure we are proposing is the conjecture that the individual text patterns appearing in the document are statistically independent (or, at least, uncorrelated), whereas the color channels, where all the features are mixed, are strictly correlated to one another. If, as we hypothesize, the color appearance of the document comes from a linear (though unknown) mixture of all the individual patterns, the output images obtained by decorrelating numerically the color channel information are copies of the individual patterns mixed in the original. Diverse mathematical approaches can be adopted to reach this goal. From our experiments, even when the linearity and decorrelation hypotheses are not verified, it can happen that the underwritten text is totally separated from all the other patterns. This would solve the problem under an image processing point of view. In some cases, however, the text to be read can still appear to be superimposed to other features. Also, scholarship needs could suggest to display all the features together. In these cases, some of the output channels can be used to build a pseudocolor image where everything is visible, but the interesting features are highlighted and well distinguishable from the interfering patterns. Our experimental results show that, by following this strategy, the readability of palimpsests can be highly improved by digital image processing even when specialized image capture facilities are not available.Source: 4th International Congress on Science and Technology for the Safeguard of Cultural Heritage in the Mediterranean Basin, pp. 199–200, Cairo, Egypt, 6-8 December 2009

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2009 Contribution to conference Restricted

Agostino Rampone e il brevetto del 1879 sugli strumenti a fiato metallici a doppia parete
Carreras F.
Wind instruments built using two coaxial pipes have introduced in Europe at the beginning of hte XIXth century. In Italy the patent by Agostino Rampone iin 1879 is the first example of the original application of these ideas to metal wind musical instruments. Other makers followed his example in the last decades of the century and in the eraly XXth century.Source: Sedicesimo Convegno Annuale SIdM, Roma, 30 ottobre 2009

See at: CNR ExploRA Restricted