Search results for " processing"
showing 10 items of 7549 documents
SVM approximation for real-time image segmentation by using an improved hyperrectangles-based method
2003
A real-time implementation of an approximation of the support vector machine (SVM) decision rule is proposed. This method is based on an improvement of a supervised classification method using hyperrectangles, which is useful for real-time image segmentation. The final decision combines the accuracy of the SVM learning algorithm and the speed of a hyperrectangles-based method. We review the principles of the classification methods and we evaluate the hardware implementation cost of each method. We present the combination algorithm, which consists of rejecting ambiguities in the learning set using SVM decision, before using the learning step of the hyperrectangles-based method. We present re…
Learning by the Process of Elimination
2002
AbstractElimination of potential hypotheses is a fundamental component of many learning processes. In order to understand the nature of elimination, herein we study the following model of learning recursive functions from examples. On any target function, the learning machine has to eliminate all, save one, possible hypotheses such that the missing one correctly describes the target function. It turns out that this type of learning by the process of elimination (elm-learning, for short) can be stronger, weaker or of the same power as usual Gold style learning.While for usual learning any r.e. class of recursive functions can be learned in all of its numberings, this is no longer true for el…
Upport vector machines for nonlinear kernel ARMA system identification.
2006
Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…
Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples
2014
Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle …
Estimation of confidence limits for descriptive indexes derived from autoregressive analysis of time series: Methods and application to heart rate va…
2017
The growing interest in personalized medicine requires making inferences from descriptive indexes estimated from individual recordings of physiological signals, with statistical analyses focused on individual differences between/within subjects, rather than comparing supposedly homogeneous cohorts. To this end, methods to compute confidence limits of individual estimates of descriptive indexes are needed. This study introduces numerical methods to compute such confidence limits and perform statistical comparisons between indexes derived from autoregressive (AR) modeling of individual time series. Analytical approaches are generally not viable, because the indexes are usually nonlinear funct…
DRESS: A Distributed RMS Evaluation Simulation Software
2020
Distributed environments consist of a huge number of entities that cooperate to achieve complex goals. When interactions occur between unknown parties, intelligent techniques for estimating agent reputations are required. Reputation management systems (RMS's) allow agents to perform such estimation in a cooperative way. In particular, distributed RMS's exploit feedbacks provided after each interaction and allow prediction of future behaviors of agents. Such systems, in contrast to centralized RMSs, are sensitive to fake information injected by malicious users; thus, predicting the performance of a distributed RMS is a very challenging task. Although many existing works have addressed some c…
A GPU-Based DVC to H.264/AVC Transcoder
2010
Mobile to mobile video conferencing is one of the services that the newest mobile network operators can offer to users With the apparition of the distributed video coding paradigm which moves the majority of complexity from the encoder to the decoder, this offering can be achieved by introducing a transcoder This device has to convert from the distributed video coding paradigm to traditional video coding such as H.264/AVC which is formed by simpler decoders and more complex encoders, and allows to the users to execute only the low complex algorithms In order to deal with this high complex video transcoder, this paper introduces a graphics processing unit based transcoder as base station The…
Restoration of Videos Degraded by Local Isoplanatism Effects in the Near-Infrared Domain
2008
When observing a scene horizontally at a long distance in the near-infrared domain, degradations due to atmospheric turbulence often occur. In our previous work, we presented two hybrid methods to restore videos degraded by such local perturbations. These restoration algorithms take advantages of a space-time Wiener filter and a space-time regularization by the Laplacian operator. Wiener and Laplacian regularization results are mixed differently depending on the distance between the current pixel and the nearest edge point. It was shown that a gradation between Wiener and Laplacian areas improves results quality, so that only the algorithm using a gradation will be used in this article. In …
Extension of luminance component based demosaicking algorithm to 4- and 5-band multispectral images
2021
Abstract Multispectral imaging systems are currently expanding with a variety of multispectral demosaicking algorithms. But these algorithms have limitations due to the remarkable presence of artifacts in the reconstructed image. In this paper, we propose a powerful multispectral image demosaicking method that focuses on the G band and luminance component. We've first identified a relevant 4-and 5-band multispectral filter array (MSFA) with the dominant G band and then proposed an algorithm that consistently estimates the missing G values and other missing components using a convolution operator and a weighted bilinear interpolation algorithm based on the luminance component. Using the cons…
HTLS Conductors: A Way to Optimize RES Generation and to Improve the Competitiveness of the Electrical Market—A Case Study in Sicily
2018
Stringent environmental constraints make more difficult to identify new energy corridors and build new power lines. The increase in the generation of electricity from renewable energy sources (RESs) makes the operation of electrical systems increasingly difficult in some areas. The transmission system operators (TSOs), in Italy Terna, are forced to exploit the existing overhead transmission lines, increasing the possibility of dispatching energy, in particular RES, optimizing the transmission capacity. Therefore, after a brief presentation of the Sicilian electricity system and a brief description of high-temperature low-sag (HTLS) conductors, a case study is presented. It is shown how it i…