This paper compares a family of methods for characterizing neural feature selectivity with natural stimuli in the framework of the linear-nonlinear model. In this model, the neural firing rate is a nonlinear function of a small number of relevant stimulus components. The relevant stimulus dimensions can be found by maximizing one of the family of objective functions, Rényi divergences of differ...

This paper compares a family of methods for characterizing neural feature selectivity with natural stimuli in the framework of the linear-nonlinear model. In this model, the neural firing rate is a nonlinear function of a small number of relevant stimulus components. The relevant stimulus dimensions can be found by maximizing one of the family of objective functions, Rényi divergences of differ...

This paper presents a motion estimation and segmentation algorithm based on multiple parametric model estimation that determines the a priori unknown number of motion models present in the data. The algorithm applies a quasisimultaneously parametric model fitting method based on a general Least Square fitting. Some experiments are showed in order to demonstrate the results obtained using the pr...

In Internet service market, at many places the competition occurs among internet service providers. The network suffers from congestion and users have priority to prefer that network having lowest congestion. During the repeated connecting attempt process the user has to maintain call-by-call effort. In this paper Markov chain model is used to establish a relationship between internet access tr...

This paper presents the first implementation of a new algorithm for pattern recognition in machine vision developed in our laboratory. This algorithm has been previously presented only theoretically, without practical use. In this work we applied it to the RobotCub humanoid robotics platform simulator. We used it as a base for a circular object localization within the 3D surrounding space. The ...

The relationship between the norm square of the standardized cumulative distribution and the chi-square statistic is examined using the form of the covariance matrix as well as the projection perspective. This investigation enables us to give uncorrelated components of the chi-square statistic and provide interpretation of these components as innovations standardizing the cumulative distributio...

Introduction The Least Square Fitting (LSF) method is a statistical approach used for evaluating respiratory mechanics [1]. It allows measurement of respiratory mechanics continuously at the bedside, even in presence of flow limitation [23], without the need for constant inspiratory flow rate, endinspiratory hold and end-expiratory occlusion. These features allow the application of the LSF meth...

Conventionally, dental models [1] are used to impart hand skill education to dental students; however, this method it is not always effective. Dental patient robots that simulate real human motion have been developed [2, 3]. However, these robots are rarely introduced in education because of their high cost and difficult maintenance. We have been developing HAP-DENT [4], a computerized dental t...

Feature extraction and location of eye are very important in face expression recognition, human-computer interaction, face detection and identification etc. This paper presents a new efficient method for eye location. Firstly, gradient, integral image, and Hough transform are used to obtain location and radius of the pupil. Secondly, CANNY operator and ellipse fitting of direct least square are...

Ellipse detection is a very important problem in the field of pattern recognition and computer vision. The existing algorithms often use a bottom-up strategy to combine edge points or elliptical arcs into ellipses, hence limit their robustness. In this paper, we propose a fast and robust ellipse detection algorithm which can accurately detect ellipses in the images. The main idea of the propose...