In recent years, utilization of feature selection techniques has become an essential requirement for processing and model construction in different scientific areas. In the field of software project effort estimation, the need to apply dimensionality reduction and feature selection methods has become an inevitable demand. The high volumes of data, costs, and time necessary for gathering data , ...

Hand pose estimation has matured rapidly in recent years. The introduction of commodity depth sensors and a multitude of practical applications have spurred new advances. We provide an extensive analysis of the state-of-the-art, focusing on hand pose estimation from a single depth frame. To do so, we have implemented a considerable number of systems, and will release all software and evaluation...

OVERWHELMING EVIDENCE DOCUMENTS a tendency toward cost and effort overruns in software projects. On average, this overrun seems to be around 30 percent.1 Furthermore, comparing the estimation accuracy of the 1980s with that reported in more recent surveys suggests that the estimation accuracy hasn’t changed much since then. (The only analyses that suggest a strong improvement in estimation accu...

We devise a new approach for non-parametric adaptive spectral analysis method, which is called the Adaptive Tuning Amplitude and Phase Estimation (ATAPES) method. The main advantage of the ATAPES algorithm is its elimination of biased estimation results in APES method, which is biased peak location and corresponding biased amplitude estimation problem. Therefore, ATAPES method provides more acc...

In this paper we consider the task of articulated 3D human pose estimation in challenging scenes with dynamic background and multiple people. Initial progress on this task has been achieved building on discriminatively trained part-based models that deliver a set of 2D body pose candidates that are then subsequently refined by reasoning in 3D [1, 4, 5]. The performance of such methods is limite...

A recent work explicitly models the discontinuous motion estimation problem in the frequency domain where the motion parameters are estimated using a harmonic retrieval approach. The vertical and horizontal components of the motion are independently estimated from the locations of the peaks of respective periodogram analyses and they are paired to obtain the motion vectors using a procedure pro...

objective: electroencephalogram is a reliable reflection of many physiological factors modulating the brain. the bispectrum is very useful for analyzing non-gaussian signals such as eeg, and detecting the quadratic phase coupling between distinct frequency components in eeg signals.the main aim of this study was to test the existence of nonlinear phase coupling within the eeg signals in a certa...

a new approach is introduced to estimate the formal information of neurons. formal information, mainly discusses about the aspects of the response that is related to the stimulus. estimation is based on introducing a mathematical nonlinear model with hammerstein-wiener system estimator. this method of system identification consists of three blocks to completely describe the nonlinearity of inpu...

‎the aim of this paper is to study distribution of ratios of generalized order statistics from pareto distribution. parameter estimation of pareto distribution based on generalized order statistics and ratios of them have been obtained. inferences using method of moments and unbiased estimator have been obtained to develop point estimations. consistency of unbiased estimator has been illustrate...