… On the other hand, using Hausdorff distance based … feature selection algorithm built on fuzzy
rough set is first proposed for dimension-reduction tasks. (2) We apply Hausdorff distance to …

… distance-based feature selection methods, where a probabilistically motivated effective
distance … Some recent works [52] further investigate Hausdorff distance in group-wise matching. …

… (2) Further we will study the Hausdorff distance and improve the Hausdorff distance to
reduce the noise, occlusion, background, and other abnormal points of medical images and …

… Therefore, a new composed signature feature is … feature data, the most distinctive Hausdorff
distance is further proposed to calculate the distances of the eight-dimensional feature vector …

… Hausdorff distance instead of the (original) Hausdorff distance is that the values of the original
Hausdorff distance … The modified Hausdorff distance does not suffer from such a problem; …

… , two different distances; namely, Euclidean and Hausdorff distance measures are all …
clustering algorithm under Euclidean and Hausdorff distance measure was individually derived for …

… This paper discovers the spatial locality feature of point sets and proposes a novel search
algorithm called local start search (LSS) to compute the exact Hausdorff Distance. The LSS …

… Thus, we propose two novel schemes to calculate the Hausdorff distance and its … two
forms of Hausdorff distance between SVNSs based on the definition of Hausdorff metric …

… distance established in this paper is the first work used in the world of feature selection. In
… As a result, from what has been explained about the Euclidean and Hausdorff distances, it …

… This study focuses on evaluating the stability of feature selection techniques with respect …
feature selection methods including variance thresholds, edit distance, and Hausdorff distance …