Pages that link to "Item:Q2256740"
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The following pages link to A sufficient condition for the convergence of the mean shift algorithm with Gaussian kernel (Q2256740):
Displaying 18 items.
- A note on the convergence of the mean shift (Q877126) (← links)
- On some convergence properties of the subspace constrained mean shift (Q898066) (← links)
- On the weak convergence and central limit theorem of blurring and nonblurring processes with application to robust location estimation (Q900800) (← links)
- A convergence theorem for graph shift-type algorithms (Q1669601) (← links)
- Convergence and stability analysis of mean-shift algorithm on large data sets (Q1747575) (← links)
- Dynamics of a mean-shift-like algorithm and its applications on clustering (Q1941687) (← links)
- The mean shift algorithm and its relation to kernel regression (Q1991846) (← links)
- Mixture model modal clustering (Q1999447) (← links)
- Modified subspace constrained mean shift algorithm (Q2038208) (← links)
- Space partitioning and regression maxima seeking via a mean-shift-inspired algorithm (Q2106775) (← links)
- Asymptotic stability of equilibrium points of mean shift algorithm (Q2339935) (← links)
- Analyzing animal escape data with circular nonparametric multimodal regression (Q2686023) (← links)
- (Q2953630) (← links)
- A convergence proof of multi-view kernel \(K\)-means clustering algorithm (Q3132381) (← links)
- (Q5159428) (← links)
- Robust Clustering Method in the Presence of Scattered Observations (Q5380442) (← links)
- A class of nonparametric mode estimators (Q5866159) (← links)
- Modal clustering of matrix-variate data (Q6106167) (← links)
