text stringlengths 0 4.09k |
|---|
Abstract: A field known as Compressive Sensing (CS) has recently emerged to help address the growing challenges of capturing and processing high-dimensional signals and data sets. CS exploits the surprising fact that the information contained in a sparse signal can be preserved in a small number of compressive (or rand... |
Title: The Influence of Intensity Standardization on Medical Image Registration |
Abstract: Acquisition-to-acquisition signal intensity variations (non-standardness) are inherent in MR images. Standardization is a post processing method for correcting inter-subject intensity variations through transforming all images from the given image gray scale into a standard gray scale wherein similar intensit... |
Title: Ball-Scale Based Hierarchical Multi-Object Recognition in 3D Medical Images |
Abstract: This paper investigates, using prior shape models and the concept of ball scale (b-scale), ways of automatically recognizing objects in 3D images without performing elaborate searches or optimization. That is, the goal is to place the model in a single shot close to the right pose (position, orientation, and ... |
Title: A Minimum Relative Entropy Controller for Undiscounted Markov Decision Processes |
Abstract: Adaptive control problems are notoriously difficult to solve even in the presence of plant-specific controllers. One way to by-pass the intractable computation of the optimal policy is to restate the adaptive control as the minimization of the relative entropy of a controller that ignores the true plant dynam... |
Title: An Improved DC Recovery Method from AC Coefficients of DCT-Transformed Images |
Abstract: Motivated by the work of Uehara et al. [1], an improved method to recover DC coefficients from AC coefficients of DCT-transformed images is investigated in this work, which finds applications in cryptanalysis of selective multimedia encryption. The proposed under/over-flow rate minimization (FRM) method emplo... |
Title: Cuspidal and Noncuspidal Robot Manipulators |
Abstract: This article synthezises the most important results on the kinematics of cuspidal manipulators i.e. nonredundant manipulators that can change posture without meeting a singularity. The characteristic surfaces, the uniqueness domains and the regions of feasible paths in the workspace are defined. Then, several... |
Title: Position Analysis of the RRP-3(SS) Multi-Loop Spatial Structure |
Abstract: The paper presents the position analysis of a spatial structure composed of two platforms mutually connected by one RRP and three SS serial kinematic chains, where R, P, and S stand for revolute, prismatic, and spherical kinematic pair respectively. A set of three compatibility equations is laid down that, fo... |
Title: Online Distributed Sensor Selection |
Abstract: A key problem in sensor networks is to decide which sensors to query when, in order to obtain the most useful information (e.g., for performing accurate prediction), subject to constraints (e.g., on power and bandwidth). In many applications the utility function is not known a priori, must be learned from dat... |
Title: Thai Rhetorical Structure Analysis |
Abstract: Rhetorical structure analysis (RSA) explores discourse relations among elementary discourse units (EDUs) in a text. It is very useful in many text processing tasks employing relationships among EDUs such as text understanding, summarization, and question-answering. Thai language with its distinctive linguisti... |
Title: Measures of Analysis of Time Series (MATS): A MATLAB Toolkit for Computation of Multiple Measures on Time Series Data Bases |
Abstract: In many applications, such as physiology and finance, large time series data bases are to be analyzed requiring the computation of linear, nonlinear and other measures. Such measures have been developed and implemented in commercial and freeware softwares rather selectively and independently. The Measures of ... |
Title: Probabilistic Recovery of Multiple Subspaces in Point Clouds by Geometric lp Minimization |
Abstract: We assume data independently sampled from a mixture distribution on the unit ball of the D-dimensional Euclidean space with K+1 components: the first component is a uniform distribution on that ball representing outliers and the other K components are uniform distributions along K d-dimensional linear subspac... |
Title: Computationally Efficient Estimation of Factor Multivariate Stochastic Volatility Models |
Abstract: An MCMC simulation method based on a two stage delayed rejection Metropolis-Hastings algorithm is proposed to estimate a factor multivariate stochastic volatility model. The first stage uses kstep iteration towards the mode, with k small, and the second stage uses an adaptive random walk proposal density. The... |
Title: Dire n'est pas concevoir |
Abstract: The conceptual modelling built from text is rarely an ontology. As a matter of fact, such a conceptualization is corpus-dependent and does not offer the main properties we expect from ontology. Furthermore, ontology extracted from text in general does not match ontology defined by expert using a formal langua... |
Title: On the Stability of Empirical Risk Minimization in the Presence of Multiple Risk Minimizers |
Abstract: Recently Kutin and Niyogi investigated several notions of algorithmic stability--a property of a learning map conceptually similar to continuity--showing that training-stability is sufficient for consistency of Empirical Risk Minimization while distribution-free CV-stability is necessary and sufficient for ha... |
Title: Intrinsic dimension estimation of data by principal component analysis |
Abstract: Estimating intrinsic dimensionality of data is a classic problem in pattern recognition and statistics. Principal Component Analysis (PCA) is a powerful tool in discovering dimensionality of data sets with a linear structure; it, however, becomes ineffective when data have a nonlinear structure. In this paper... |
Title: Bayesian Inference |
Abstract: This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal method for summarising uncertainty and making estimates and predictions using probability statements conditional on observed data and an assumed model (Gelman 2008). The Bayesian perspective is thus applicable to... |
Title: Estimating Bayesian networks for high-dimensional data with complex mean structure and random effects |
Abstract: The estimation of Bayesian networks given high-dimensional data, in particular gene expression data, has been the focus of much recent research. Whilst there are several methods available for the estimation of such networks, these typically assume that the data consist of independent and identically distribut... |
Title: Reverse Engineering Financial Markets with Majority and Minority Games using Genetic Algorithms |
Abstract: Using virtual stock markets with artificial interacting software investors, aka agent-based models (ABMs), we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By optimizing the similarity betwe... |
Title: Detection of Microcalcification in Mammograms Using Wavelet Transform and Fuzzy Shell Clustering |
Abstract: Microcalcifications in mammogram have been mainly targeted as a reliable earliest sign of breast cancer and their early detection is vital to improve its prognosis. Since their size is very small and may be easily overlooked by the examining radiologist, computer-based detection output can assist the radiolog... |
Title: The Fast Haar Wavelet Transform for Signal & Image Processing |
Abstract: A method for the design of Fast Haar wavelet for signal processing and image processing has been proposed. In the proposed work, the analysis bank and synthesis bank of Haar wavelet is modified by using polyphase structure. Finally, the Fast Haar wavelet was designed and it satisfies alias free and perfect re... |
Title: Vision Based Game Development Using Human Computer Interaction |
Abstract: A Human Computer Interface (HCI) System for playing games is designed here for more natural communication with the machines. The system presented here is a vision-based system for detection of long voluntary eye blinks and interpretation of blink patterns for communication between man and machine. This system... |
Title: Modeling of Human Criminal Behavior using Probabilistic Networks |
Abstract: Currently, criminals profile (CP) is obtained from investigators or forensic psychologists interpretation, linking crime scene characteristics and an offenders behavior to his or her characteristics and psychological profile. This paper seeks an efficient and systematic discovery of nonobvious and valuable pa... |
Title: A Generalization of the Chow-Liu Algorithm and its Application to Statistical Learning |
Abstract: We extend the Chow-Liu algorithm for general random variables while the previous versions only considered finite cases. In particular, this paper applies the generalization to Suzuki's learning algorithm that generates from data forests rather than trees based on the minimum description length by balancing th... |
Title: Effect of Wind Intermittency on the Electric Grid: Mitigating the Risk of Energy Deficits |
Abstract: Successful implementation of California's Renewable Portfolio Standard (RPS) mandating 33 percent renewable energy generation by 2020 requires inclusion of a robust strategy to mitigate increased risk of energy deficits (blackouts) due to short time-scale (sub 1 hour) intermittencies in renewable energy sourc... |
Title: Operator norm convergence of spectral clustering on level sets |
Abstract: Following Hartigan, a cluster is defined as a connected component of the t-level set of the underlying density, i.e., the set of points for which the density is greater than t. A clustering algorithm which combines a density estimate with spectral clustering techniques is proposed. Our algorithm is composed o... |
Title: Automatic diagnosis of retinal diseases from color retinal images |
Abstract: Teleophthalmology holds a great potential to improve the quality, access, and affordability in health care. For patients, it can reduce the need for travel and provide the access to a superspecialist. Ophthalmology lends itself easily to telemedicine as it is a largely image based diagnosis. The main goal of ... |
Title: Medical Image Compression using Wavelet Decomposition for Prediction Method |
Abstract: In this paper offers a simple and lossless compression method for compression of medical images. Method is based on wavelet decomposition of the medical images followed by the correlation analysis of coefficients. The correlation analyses are the basis of prediction equation for each sub band. Predictor varia... |
Title: Application of k Means Clustering algorithm for prediction of Students Academic Performance |
Abstract: The ability to monitor the progress of students academic performance is a critical issue to the academic community of higher learning. A system for analyzing students results based on cluster analysis and uses standard statistical algorithms to arrange their scores data according to the level of their perform... |
Title: Feature Level Fusion of Face and Fingerprint Biometrics |
Abstract: The aim of this paper is to study the fusion at feature extraction level for face and fingerprint biometrics. The proposed approach is based on the fusion of the two traits by extracting independent feature pointsets from the two modalities, and making the two pointsets compatible for concatenation. Moreover,... |
Title: Assessment Of The Wind Farm Impact On The Radar |
Abstract: This study shows the means to evaluate the wind farm impact on the radar. It proposes the set of tools, which can be used to realise this objective. The big part of report covers the study of complex pattern propagation factor as the critical issue of the Advanced Propagation Model (APM). Finally, the reader ... |
Title: On computational tools for Bayesian data analysis |
Abstract: While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the current chapter details its practical aspects through a review of the computational methods available for approximating Bayesian procedures. Recent innovations like Monte Carlo Markov chain, sequential Monte Carlo me... |
Title: Bayesian computational methods |
Abstract: In this chapter, we will first present the most standard computational challenges met in Bayesian Statistics, focussing primarily on mixture estimation and on model choice issues, and then relate these problems with computational solutions. Of course, this chapter is only a terse introduction to the problems ... |
Title: Evolutionary Stochastic Search for Bayesian model exploration |
Abstract: Implementing Bayesian variable selection for linear Gaussian regression models for analysing high dimensional data sets is of current interest in many fields. In order to make such analysis operational, we propose a new sampling algorithm based upon Evolutionary Monte Carlo and designed to work under the "lar... |
Title: Multibiometrics Belief Fusion |
Abstract: This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.