The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Various computer simulations are used to illustrate the performance of a particular protocol. However, the number of parameters and logical layers considered is the key to getting accurate results. We extend our previous work of Complete Transmission Acknowledgement Scheme (CTAS) by running the proposed model on top of the physical layer. Effect of noise and the standard Orthogonal Frequency Division...
We propose a new method for fitting an ellipse to a point sequence extracted from an image. This method can fit an ellipse if a point sequence consists of elliptic arcs and non-elliptic arcs such as line segments. Assuming that input points are spatially connected, we iteratively select inlier points and fit an ellipse to them by computing curvatures of the residual graph. By using simulated data...
In day to day life, digital mediated interactions and communications being an important constituent. The expeditious growth of electronic communications such as E-mails, micro blogs, SMS and chats etc has fabricated extensively noisy forms of text. It predominantly in young urbanités. The tremendous growth of noises in text are due to a variety of factors, such as the small number of characters allowed...
The RANdom SAmple Consensus (RANSAC) algorithm, as a robust parameter estimator, has been widely used to remove gross errors. However, there is less work on analyzing the uncertainty produced by the RANSAC. This paper fills this gap by presenting an uncertainty estimation algorithm for the RANSAC. Based on a thorough analysis on the uncertainty of the model parameters generated during the random hypothesis...
In this paper, we propose a new method for designing the variation restoration model which uses the noise evaluation to decide the approximation term and the information of geometrical structures in the blurred and noised images to choose the regularization term. We adjust the measurement for the approximation term based on the noise variance in the degraded image. By computing the mean curvature...
The segmentation of brain magnetic resonance (MR) images into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) has been an intensive studied area in the medical image analysis community. The Gaussian mixture model (GMM) is one of the most commonly used model to represent the intensity of different tissue types. However, as a histogram-based model, the spatial relationship between...
Model scoring in latent factor models is essential for a broad spectrum of applications such as clustering, change point detection or model order estimation. In a Bayesian setting, model selection is achieved via computation of the marginal likelihood. However, this is a typically challenging task as it involves calculation of a multidimensional integral over all the latent variables. In this paper,...
A poor choice of importance density can have detrimental effect on the efficiency of a particle filter. While a specific choice of proposal distribution might be close to optimal for certain models, it might fail miserably for other models, possibly even leading to infinite variance. In this paper we show how mixture sampling techniques can be used to derive robust and efficient particle filters,...
This paper presents a novel method to perform the outlier rejection task between two different views of a camera rigidly attached to an Inertial Measurement Unit (IMU). Only two feature correspondences and gyroscopic data from IMU measurerments are used to compute the motion hypothesis. By exploiting this 2-point motion parametrization, we propose two algorithms to remove wrong data associations in...
We present a new general and language independent approach to the noisy text correction problem developed and implemented in the framework of the CULTURA project. We briefly describe the core candidate generator, REBELS, the complete system concept, its efficient implementation based on functional automata and its immediate applications. The quality of the whole system is empirically established in...
We investigate the effects of missing observations on the robust Bayesian model for spectral analysis introduced by Christmas [2013]. The model assumes Student-t distributed noise and uses an automatic relevance determination prior on the precisions of the amplitudes of the component sinusoids and it is not obvious what their effect will be when some of the otherwise temporally uniformly sampled data...
The utilization of the Return Channel Satellite (RCS) in DVB systems allows a bi-directional communication via satellite. With this particular characteristic, DVB-RCS systems promoted its enormous diffusion in the commercial area and the academic research interest and, in this context, it is very important to test DVB-RCS systems using an efficient satellite channel model. Many channel models have...
Accuracy of 3-D models is important in model-based camera tracking. However, their precise modeling requires delicate procedures. On the other hand, end-users are difficult to perceive tracking errors, which are caused by a certain level of modeling errors. Therefore, human perceptual errors can be different from real tracking errors. In this paper, we analyze the tolerance of modeling errors by comparing...
This paper introduces a novel technique to track structures in time evolving graphs. The method is based on a parameter free approach for three-dimensional co-clustering of the source vertices, the target vertices and the time. All these features are simultaneously segmented in order to build time segments and clusters of vertices whose edge distributions are similar and evolve in the same way over...
For high performance analog and mixed-signal products, production test is a significant contributor to the recurring manufacturing cost. For high resolution ADCs, the cost of build can be dominated by test cost, of which linearity test cost is often the largest component. This paper introduces a new algorithm that dramatically reduces ADC linearity test cost. The algorithm takes a system identification...
Segmentation of a time series attempts to divide it into homogeneous subsequences, such that each of these segments are different from each other. A typical segmentation framework involves selecting a model that is used to represent the segment. In this paper, we investigate segmentation scores based on difference between models and propose two approaches for normalizing the difference based score...
This paper investigates the validity of the analytical framework for bias and variance in kinetic parameter estimations. Analytical computation of bias and variance is compared against Monte Carlo simulations for two different compartment models at different noise levels. Difference between the estimated and measured variance increases with the level of noise and complexity of the compartment model...
Functional imaging serves as an important supplement to anatomical imaging modalities such as MR and CT in modern health care. In perfusion CT (CTP), hemodynamic parameters are derived from the tracking of the first-pass of the contrast bolus entering a tissue region of interest. In practice, however, the post-processed parametric maps tend to be noisy, especially in low-dose CTP, in part due to the...
Standard analysis techniques for Functional Magnetic Resonance Imaging (fMRI) assume a linear, time invariant model of underlying signal behaviour. These assumptions are valid for some but not all data. Hence each model characteristic should be formally tested for its validity when analysing particular data. Diagnosing model violations is a necessary step in statistical modeling but is not yet common...
We present a new method for the detection of multiple homographies in image pairs. Our aim is to show that we can approach the optimal solution in a short time using an approach based on the well-known RANSAC algorithm. Given feature correspondences between two similar images, our algorithm iteratively generates homography hypotheses using a suitable sampling, optimizes the promising hypotheses and...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.