Adaptive Mean Shift-Based Clustering
Fajie Li, Reinhard Klette · 2008
Abstract. This report proposes an adaptive mean shift clustering algorithm. Its application is demonstrated for simulated data, by finding old clusters which are highly overlapping. The obtained clustering result is actually close to an estimated upper bound, derived for those simulated data elsewhere. Key words: clustering, mean shift based-clustering, recovery rate