resampling method
Unified piecewise epipolar resampling method for pushbroom satellite images
... epipolar resampling method is proposed to generate stereo image pairs with zero y-parallax, a square pixel scale, and proportionality between x-parallax disparity and ...the method are presented ...
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A prediction based resampling method for estimating the number of clusters in a dataset
... setting. Resampling methods such as bagging [13] and boosting [14,15] have been applied success- fully in the field of supervised learning to improve prediction ...novel resampling method, Clest, ...
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ENSO conditioned weather resampling method for seasonal ensemble streamflow prediction
... subsampler–resampler method also has some prac- tical advantages over alternative ...resampler method allows for a parallel sampling of non-meteorological variables from the historical record, with ...
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Best Parameter Interval for Ridge Estimates by Resampling Method
... Data used for this analysis, household data, consists of some familiar variables which are correlated to each other more or less. The response variable was Household Expenditure (HHEXP) with some selected explanatory ...
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Treating phenotype as given: a simple resampling method for genome wide association studies
... a resampling procedure to assess this statistic ’ s genome-wide ...This method has been applied to replicate 2 of the Genetic Analysis Workshop 17 simulated data on unrelated individuals in an attempt to ...
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Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models
... on resampling methods, enable us to consider categorical transformations as more flexible in order to explore the unknown shape of the effect between an explanatory and a dependent ...the resampling ...
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Confidence intervals construction for difference of two means with incomplete correlated data
... Although testing equivalence of two correlated means with incomplete data has been studied, there is little work done on their interval estimators. To address the issue, this paper proposes various interval estimators of ...
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Improving the accuracy of likelihood based inference in meta analysis and meta regression
... Figure 4 and Figure 5 show the full results from the simulation study in § 4.1 of the paper. Specifically, Figure 4 and Figure 5 include empirical coverage probabilities of two-sided confi- dence intervals for increasing ...
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Improved Resampling Algorithms Based on Deterministic and Partial Resampling
... and resampling step [1]. The resampling step is critical in every implementation of particle filtering, because without it the weights of most particles quickly become so small and will be given up, which ...
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Fingerprint resampling: A generic method for efficient resampling
... In resampling methods, such as bootstrapping or cross validation, a very similar computational problem (usually an optimization procedure) is solved over and over again for a set of very similar data ...whole ...
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Adaptive memory-based single distribution resampling for particle filter
... distribution resampling called traditional variation ...multinomial resampling within the residual resampling algorithm was omitted, and the implementation of the resampling was done in one ...
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A Novel Approach for Waveform Compression
... the resampling size of wave file is decreased, but it also leads to distortion in the background of ...of Resampling method. Resampling method is used to decrease the size of wave file ...
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PRL RR 26 pdf
... the method of quadratic resampling (QR), a new powerful error reduction technique for Monte Carlo ...Quadratic resampling can be efficiently combined with classical variance reduction methods such as ...
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Title: A Review on Rapidly Convergence Approach for Handling Class Imbalance Data Set
... Chawla proposed Synthetic Minority Over-sampling Technique (SMOTE) [8] an over-sampling approach in which the minority class is over-sampled with replacement. The SMOTE algorithm is used to generate artificial samples of ...
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Identifying a possible stratification phenomenon in ionospheric F2 layer using the data observed by the DEMETER satellite: method and results
... A method therefore is proposed in this paper which can compare the in situ electron density data obtained at different altitudes and identify their ...this method, the in situ electron density data, ...
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Pan-Sharpening of Multispectral Imagery Using Content-Specific Orthogonal Linear Transform
... a method for merging a set of multispectral bands with the higher spatially resolved panchromatic ...pan-sharpening method were carried out with the use of data from modern very high resolution satellite ...
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A Hybrid Feature Selection Method to Improve Performance of a Group of Classification Algorithms
... costly method due to its comprehensive search on the feature ...accurate method and also reducing its computational cost, we used a hybrid strategy in the second phase of the proposed ...wrapper ...
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Semi-Analytic Resampling in Lasso
... be adopted. In this study, Gaussian approximation is used in conjunction with the so-called cavity method, providing a message passing type algorithm. Its dynamical behavior is analyzed by the so-called state ...
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Translation Model Adaptation by Resampling
... It is common practice to use a mixture language model with coefficients that are optimized on the development data, i.e. by these means on the do- main of the translation task. Domain adaptation seems to be more tricky ...
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Video Transcoder in DCT-Domain Spatial Resolution Reduction Using Low-Complexity Motion Vector Refinement Algorithm
... 16(d), respectively. In Table 3, we also show the average PSNR and bit-rate at QP = 10 for three sequences. The objective of HFMR is to ensure consistent quality among various video sequences. Thus, slight modification ...
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