kernel estimation
Deblurring of License Plate Image using Blur Kernel Estimation
... estimate kernel from the blurred image and apply a non-blind image de-blurring (NBID) algorithm recursively to approach the true solution ...accurate kernel, then NBID algorithm is only applied once to ...
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Kernel Estimation and Model Combination in A Bandit Problem with Covariates
... the kernel estimation based randomized allocation strategy can be quite flexible with wide potential practical ...the kernel estimation into a UCB-type algorithm with randomization and show ...
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Deblurring of Noisy or Blurred Image by Using Kernel Estimation Algorithm
... the kernel estimated at the current level to initialize the next finer ...the kernel, the global shape of the kernel at a fine level to be similar to the shape at its coarser ...a kernel mask ...
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Kernel Estimation in Line Transect Sampling for Parametric Model
... nonparametric estimation methods. In this paper, we present kernel method to propose new estimator of the propose population ...density. Kernel estimation method is used due to avoid the ...
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Deblurring license plate images with kernel estimation
... the kernel can be approximated by linear uniform motion blur ...blur kernel estimation can be reduced to the estimation of two parameters in the linear motion kernel: angle (θ ) and ...
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Kernel estimation and display of a five-dimensional conditional intensity function
... the estimation of a complex intensity function dependent on the past history of the process as in (2) now reduces to the estimation of the intensity function of an inhomogeneous Poisson process, in- ...
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Super-resolution via a fast deconvolution with kernel estimation
... In this paper, we presented a simple and effective sin- gle image super-resolution method. Our method was motivated by a fast image upsampling method, but we differently studied the estimated error of the blur ker- nel ...
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Nonparametric Kernel estimation of annual maximum stream flow quantiles.
... of kernel function is not critical since various kernels lead to comparable estimates ...the kernel does not important, and the shape of kernel does not affect extrapolation accuracy ...
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Global Polynomial Kernel Hazard Estimation
... The general approach in non-parametric kernel estimation is to divide the esti- mation error into a stable part and a variable part. Under the standard conditions in that smoothing theory (cf. e.g. Nielsen ...
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Kernel density estimation on the torus
... density kernel estima- tor whose weight functions are based on some well-known circular ...of kernel estimation of any mixed partial derivative of ...multivariate kernel density derivative ...
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Sequential Fixed-width Confidence Bands for Kernel Regression Estimation
... performing reliably over all since its variance can fail to exist in random designs. Also, the Nadaraya-Watson es- timator retains some optimality properties as exposed in Hardle and Marron (1985). Methods for obtaining ...
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nihms935418.pdf
... semiparametric estimation of the AFT model is highly challenging, even in the case of right-censored data (Prentice, 1978; Buckley and James, 1979; Tsiatis, 1990; Lai and Ying, 1991; Zeng and Lin, 2007; Lin and ...
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Problems in density estimation for independent and dependent data
... of kernel density estimation are not new, having been proposed by Rosenblatt [20] and extended by Parzen ...Thus kernel estimation has captured the imagination of statisticians searching for ...
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Some Improvement on Convergence Rates of Kernel Density Estimator
... of kernel or- der using Fourier transformation. Variable kernel estimation in [4] successfully reduced the bias by employing larger smoothing parameters in low density regions, while [5] introduced ...
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The trade-off between fix rate and tracking duration on estimates of home range size and habitat selection for small vertebrates
... the estimation of habitat selection by providing an individ- ual measure of habitat availability ...as estimation method and bandwidth parameter [41], it can then influence the strength of habitat selection ...
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Forest Fire Risk Mapping by Kernel Density Estimation
... Koutsias, N., Kalabokidis, K. D., Allgöwer, B., 2004: Fire occurrence patterns at landscape level: beyond positional accuracy of ignition points with kernel density estimation methods. Natural Resource ...
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Kernel Based Object Counting Using Density Estimation
... Density Map Estimation deals with estimation of density at each pixel location of an image. This method provides spatial information about object location. From the view point of pedestrian counting, this ...
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Performance Evaluation of Various Functions for Kernel Density Estimation
... nine kernel func- tions for ...nine kernel functions for MILD and SEVERE respectively and axis convention is the same as the one in ...Uniform kernel was the worst and cosine kernel seems to ...
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An Iterative Surface Evolution Algorithm for Multiview Stereo
... 2.1. Visual Hull Construction. The first step of our algorithm is to obtain an initial shape estimation by constructing a visual hull. Visual hull is an outer approximation of the observed solid constructed as the ...
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Control points based on network analysis for hot spots by qualified theft, City of Aguascalientes, Mexico, 2011 – 2017.
... The difference between the number of segments greater from case 1 to case 2 stands out that it is generated by a particular calculation for each case. Through the following image, it will be possible to identify that the ...
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