… distances, which may be affected by outliers, we consider the median or, in general, the k-th
smallest distance… ≤k≤|A|, we define the directed partial Hausdorff distance from A to B to be …

… They are feature selection, similarity measure and the parameter optimization. A corner is a
point that can be extracted consistently over different views, and there is enough information …

… ranking we apply an alternative of the Spearman’s Footrule ([14]), a metric based on the
Hausdorff distance, which can be used for measuring the stability of ranking for partial ranked …

… distance measure, that has been shown to perform … feature selection using the Hausdorff
distance (FSH) method is presented after a brief introduction to the Hausdorff distance measure. …

… In this paper, a well-known distance measure termed as modified Hausdorff distance (MHD)
is proposed for automatic ear localization. We introduced the MHD to decrease the effect of …

… the forward feature selection [41] and the leave-one-out 1-NN error as a selection criterion. …
Then, the Hausdorff distance between them is computed as d H ( A , B ) = max { d H ▹ ( A , B ) …

… distance between two images are computed based on the SIFT features using Hausdorff
distance … The embedding of the given face image is similarly computed using Hausdorff distance…

… on Hausdorff distance is one of the major algorithms. In this paper, we presents a modified
Hausdorff distance (… algorithms which are based on Hausdorff distance. This algorithm uses …

… the complex nonlinear relationships between high and low dimensional features [37]. In this
paper, the DBN and Hausdorff distance (HD) based method for evaluating the health status …

… Usually, redundant/irrelevant features can increase the … The purpose of feature selection
(FS) is to choose a feature … Jensen, “Feature selection for high dimensional imbalanced …