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We present a method to learn and recognize object class
models from unlabeled and unsegmented cluttered scenes
in a scale invariant manner. Objects are modeled as flexible
constellations of parts. A probabilistic representation is
used for al
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一种多站测向多目标被动跟踪方法的研究,通过采用最小距离法、最大似然法等方法剔除掉虚假定位点-A multi-station finding the multi-target passive tracking method through the use of the minimum distance method, maximum likelihood method and other methods to weed out the false positioning point
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this method is called the maximum likelihood estimation method .which is used to find out the parameters of johnson distribution .
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In this paper we present Discriminative Random Fields (DRF), a discrim- inative framework for the classification of natural image regions by incor- porating neighborhood spatial dependencies in the labels as well as the observed data. The proposed mo
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a important ML estimation method for linear regression vie Maximum likelihood method
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maximum likelihood estimation method can be used to very broad estimation
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人脸识别中的光照处理方法，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，最大似然（ML）准则和最大后验概率（MAP）准则。- Face Recognition light treatment method, Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) cr
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