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22nd Iberoamerican Congress on Pattern Recognition, CIARP 2017

作者： Sad, Gonzalo D. Terissi, Lucas D. Gómez, Juan C. Laboratory for System Dynamics and Signal Processing Universidad Nacional de Rosario CIFASIS-CONICET Rosario Argentina

ISBN: (纸本)9783319751924

This paper presents an audio-visual speech classification system based on Random Forests classifiers, aiming to reduce the intra-class misclassification problems, which is a very usual situation, specially in speech recognition tasks. A novel training procedure is proposed, introducing the concept of Complementary Random Forests (CRF) classifiers. Experimental results over three audio-visual databases, show that a good performance is achieved with the proposed system for the different types of input information considered, viz., audio-only information, video-only information and fused audio-video information. In addition, these results also indicate that the proposed method performs satisfactorily over the three databases using the same configuration parameters. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Decision trees

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Modeling the relationship between regional activation and functional connectivity during wakefulness and sleep

arXiv

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arXiv 2019年

作者： Ipinã, Ignacio Perez Kehoe, Patricio Donnelly Kringelbach, Morten Laufs, Helmut Ibañez, Agustin Deco1, Gustavo Per, Yonatan Sanz Tagliazucchi, Enzo Department of Physics University of Buenos Aires National Scientific and Technical Research Council Buenos Aires Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas National Scientific and Technical Research Council Rosario Argentina Laboratory for System Dynamics and Signal Processing Universidad Nacional de Rosario Laboratory of Neuroimaging and Neuroscience INECO Foundation Rosario Rosario Department of Psychiatry University of Oxford Oxford United Kingdom Center for Music in the Brain Dept. of Clinical Medicine Aarhus University Department of Neurology University of Kiel Kiel Germany Laboratory of Experimental Psychology and Neuroscience Institute of Cognitive and Translational Neuroscience INECO Foundation Favaloro University Buenos Aires Centre of Excellence in Cognition and Its Disorders Australian Research Council Sydney Center for Social and Cognitive Neuroscience School of Psychology Universidad Adolfo Ibáñez Santiago Universidad Autónoma Del Caribe Barranquilla Colombia Center for Brain and Cognition Computational Neuroscience Group Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Institució Catalana de la Recerca i Estudis Avancats Universitat Pompeu Fabra Barcelona

Global brain activity self-organizes into discrete patterns characterized by distinct behavioral observables and modes of information processing. The human thalamocortical system is a densely connected network where local neural activation reciprocally influences coordinated collective dynamics. We introduce a semi-empirical model to investigate the relationship between regional activation and long-range functional connectivity in the different brain states visited during the natural wake-sleep cycle. Our model combines functional magnetic resonance imaging (fMRI) data, in vivo estimates of structural connectivity, and anatomically-informed priors that constrain the independent variation of regional activation. As expected, priors based on functionally coherent networks resulted in the best fit between empirical and simulated brain activity. We show that sleep progressively divided the cortex into regions presenting opposite dynamical behavior: Frontoparietal regions approached a bifurcation towards local oscillatory dynamics, while sensorimotor regions presented stable dynamics governed by noise. In agreement with human electrophysiological experiments, sleep onset induced subcortical deactivation and uncoupling, which was subsequently reversed for deeper stages. Finally, we introduced external forcing of variable intensity to simulate external perturbations, and identifiedthe key regionsespecially relevant for the recovery of wakefulness from deep sleep. Our model represents sleep as a state where long-range decoupling and regional deactivation coexist with the latent capacity for a rapid transition towards wakefulness. The mechanistic insights provided by our simulations allow the in silico parametric exploration of such transitions in terms of external perturbations, with potential applications for the control of physiological and pathological brain states. Copyright © 2019, The Authors. All rights reserved.

关键词： Chemical activation

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Online signature verification based on legendre series representation. Consistency analysis of different feature combinations

Online signature verification based on legendre series repre...

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17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012

作者： Parodi, Marianela Gómez, Juan Carlos Laboratory for System Dynamics and Signal Processing Universidad Nacional de Rosario CONICET Argentina

ISBN: (纸本)9783642332746

In this paper, orthogonal polynomial series are used to approximate the time functions associated to the signatures and the coefficients in these series are used as features to model them. A novel consistency factor is proposed to quantify the discriminative power of different combinations of time functions related to the signing process. Pen coordinates, incremental variation of pen coordinates and pen pressure are analyzed for two different signature styles, namely, Western signatures and Chinese signatures from a publicly available Signature Database. Two state-of-the-art classifiers, namely, Support Vector Machines and Random Forests are used in the verification experiments. The obtained error rates are comparable to results reported over the same signature datasets in a recent signature verification competition. © 2012 Springer-Verlag.

关键词： Orthogonal functions

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A combined SVM/Ob-based wiener model identification method

A combined SVM/Ob-based wiener model identification method

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Universite Libre de Bruxelles

作者： Gomez, Juan C. Baeyens, Enrique Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario CIFASIS CONICET Riobamba 245 Bis 2000 Rosario Argentina Instituto de las Tecnologías Avanzadas de la Producción Universidad de Valladolid Paseo del Cauce 59 47011 Valladolid Spain

ISBN: (纸本)9783902823069

A novel method, combining Support Vector Machines and Least Squares Prediction Error techniques, for the identification of the linear and nonlinear blocks in a Wiener model is presented in this paper. The identification is carried out by minimizing an augmented cost function defined as the sum of the standard structural risk function appearing in Support Vector Regression and the quadratic criterion on the prediction errors associated to Least Squares estimation methods. The properties of the proposed method are illustrated through simulation examples. © 2012 IFAC.

关键词： Support vector machines

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Online Signature Verification Based on Legendre Series Representation: Robustness Assessment of Different Feature Combinations

Online Signature Verification Based on Legendre Series Repre...

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International Workshop on Frontiers in Handwriting Recognition

作者： Marianela Parodi Juan C. Gómez Marcus Liwicki Laboratory for System Dynamics and Signal Processing FCEIA CIFASIS CONICET Universidad Nacional de Rosario Rosario Argentina German Research Center for Artificial Intelligence Kaiserslautern Germany

In this paper, orthogonal polynomials series are used to approximate the time functions associated to the signatures. The coefficients in these series expansions, computed resorting to least squares estimation techniques, are then used as features to model the signatures. Different combinations of several time functions (pen coordinates, incremental variation of pen coordinates and pen pressure), related to the signing process, are analyzed in this paper for two different signature styles, namely, Western signatures and Chinese signatures of a publicly available Signature Database. Two state-of-the-art classification methods, namely, Support Vector Machines and Random Forests are used in the verification experiments. The proposed online signature verification system delivers error rates comparable to results reported over the same signature datasets in a previous signature verification competition.

关键词： Support vector machines Radio frequency Polynomials Training Testing Least squares approximation

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A Combined SVM/OB-based Wiener Model Identification Method

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IFAC Proceedings Volumes 2012年第16期45卷 638-643页

作者： Juan C. Gómez Enrique Baeyens Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario CIFASIS CONICET Riobamba 245 Bis 2000 Rosario Argentina Instituto de las Tecnologías Avanzadas de la Producción Universidad de Valladolid Paseo del Cauce 59 47011 Valladolid Spain

关键词： system Identification Wiener Models Support Vector Machines Orthonormal Bases Expansions Nonlinear Kernel Expansions

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A DWT-SVD based perceptual image fidelity metric for watermaking schemes

A DWT-SVD based perceptual image fidelity metric for waterma...

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作者： Del Colle, Franco Gómez, Juan Carlos Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario Rosario Argentina

ISBN: (纸本)9789898425195

In this paper, a novel DWT-SVD perceptual fidelity metric for the evaluation of watermarking schemes is introduced. The proposed metric is based on a widely used Human Visual Model in the Discrete Wavelet Transform domain accounting for the frequency sensitivity, and the local luminance and contrast masking effects of the human eye. A relationship between the visual model in the DWT domain and the modification of the wavelet coefficients's singular values is derived. The proposed metric is validated through subjective assessment and its performance is compared to several state-of-the-art perceptual image distortion metrics. The paper focus on Image Adaptive Watermarking methods in the Discrete Wavelet Transform Domain since they yield better results regarding robustness and transparency than other watermarking schemes.

关键词： Discrete wavelet transforms

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A new DWT-SVD based perceptual fidelity metric for quality assessment of watermaking schemes

A new DWT-SVD based perceptual fidelity metric for quality a...

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18th European signal processing Conference, EUSIPCO 2010

作者： Del Colle, Franco Ǵomez, Juan Carlos Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario CIFASIS-CONICET Riobamba 245 Bis 2000 Rosario Argentina

A new DWT-SVD perceptual fidelity metric for the evaluation of watermarking schemes is introduced in this paper. A widely used Human Visual Model in the Discrete Wavelet Transform domain is employed by the metric to account for the frequency sensitivity, and the local luminance and contrast masking effects of the human eye. A relationship between the visual model in the DWT domain and the modification of the wavelet coefficients singular values is derived. Subjective experiments are used to validate the proposed metric, and its performance is compared to several state-of-the-art perceptual image distortion metrics. The paper focuses on Image AdaptiveWatermarking methods in the Discrete Wavelet Transform Domain since they yield better results regarding robustness and transparency than other watermarking schemes. © EURASIP, 2010.

关键词： Discrete wavelet transforms

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A NEW DWT-SVD BASED PERCEPTUAL FIDELITY METRIC FOR QUALITY ASSESSMENT OF WATERMAKING SCHEMES

A NEW DWT-SVD BASED PERCEPTUAL FIDELITY METRIC FOR QUALITY A...

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European signal processing Conference

作者： Franco Del Colle Juan Carlos Gomez Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario CIFASIS-CONICET

A new DWT-SVD perceptual fidelity metric for the evaluation of watermarking schemes is introduced in this paper. A widely used Human Visual Model in the Discrete Wavelet Transform domain is employed by the metric to account for the frequency sensitivity, and the local luminance and contrast masking effects of the human eye. A relationship between the visual model in the DWT domain and the modification of the wavelet coefficients singular values is derived. Subjective experiments are used to validate the proposed metric, and its performance is compared to several state-of-the-art perceptual image distortion metrics. The paper focuses on Image Adaptive Watermarking methods in the Discrete Wavelet Transform Domain since they yield better results regarding robustness and transparency than other watermarking schemes.

关键词： Measurement Watermarking Discrete wavelet transforms Image quality Wavelet domain Quality assessment Visualization

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A DWT-SVD based perceptual image fidelity metric for watermaking schemes

A DWT-SVD based perceptual image fidelity metric for waterma...

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International Conference on signal processing and Multimedia Applications (SIGMAP)

作者： Franco Del Colle Juan Carlos Gómez Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario Rosario Argentina CIFASIS CONICET Rosario Argentina

关键词： Measurement Watermarking Discrete wavelet transforms Wavelet domain Matrix decomposition Quantization Humans

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