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关注：1
2013-05-23 12:21
求翻译：F is the feature vector of the K type for S. Each likelihood ratio P is computed with the help of nonparametric density estimates of features from the required class(es) in the neighborhood of F. Speci cally, let D denote the set of all superpixels in the training set, and N denote the set of all superpixels in the ret是什么意思？ 待解决
 悬赏分：1
- 离问题结束还有
F is the feature vector of the K type for S. Each likelihood ratio P is computed with the help of nonparametric density estimates of features from the required class(es) in the neighborhood of F. Speci cally, let D denote the set of all superpixels in the training set, and N denote the set of all superpixels in the ret
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2013-05-23 12:21:38
F是K型为S，各似然比P ，计算与来自于F.特定美云的附近所需的类（或多个）特征的非参数密度估计的帮助的特征向量，令D表示该组的所有的
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2013-05-23 12:23:18
正在翻译，请等待...
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2013-05-23 12:24:58
F是K类型的特点传染媒介为S。 每个可能比率P在特点帮助下的非参数密度估计在F.邻里计算(从) 必需的类ES。 Speci cally，在训练集合让D表示套所有superpixels，并且N在从F的kth特点距离在a之下被设置的检索表示套所有superpixels 固定的门限T。 然后我们有
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2013-05-23 12:26:38
F 是特征向量的 s K 型每个似然比 P 计算非参数密度估计的特征借助 F.规格效法的邻域中所需的类，让 D 表示在培训组中，所有 superpixels 套和 N 表示其泰熙特征距离从 F 是低于固定阈值 T.检索集合中的所有 superpixels 的集然后我们有
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2013-05-23 12:28:18
F is the feature vector of the K type for S.Each likelihood ratio P is computed with the help of nonparametric density estimates of features from the required class(es) in the neighborhood of F.Speci cally, let D denote the set of all superpixels in the training set, and N denote the set of all supe
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