Locally Adaptive Hierarchical Cluster Termination With Application To Individual Tree Delineation

12/01/2022
by   Ashlin Richardson, et al.
0

A clustering termination procedure which is locally adaptive (with respect to the hierarchical tree of sets representative of the agglomerative merging) is proposed, for agglomerative hierarchical clustering on a set equipped with a distance function. It represents a multi-scale alternative to conventional scale dependent threshold based termination criteria.

READ FULL TEXT

page 1

page 2

page 3

page 8

research
02/25/2019

Dependent choice as a termination principle

We introduce a new formulation of the axiom of dependent choice that can...
research
12/05/2018

Termination of λΠ modulo rewriting using the size-change principle (work in progress)

The Size-Change Termination principle was first introduced to study the ...
research
11/11/2021

Hierarchical clustering by aggregating representatives in sub-minimum-spanning-trees

One of the main challenges for hierarchical clustering is how to appropr...
research
09/24/2021

Adaptive Clustering-based Reduced-Order Modeling Framework: Fast and accurate modeling of localized history-dependent phenomena

This paper proposes a novel Adaptive Clustering-based Reduced-Order Mode...
research
05/21/2019

Termination of Triangular Integer Loops is Decidable

We consider the problem whether termination of affine integer loops is d...
research
05/11/2020

Restricted Chase Termination for Existential Rules: a Hierarchical Approach and Experimentation

The chase procedure for existential rules is an indispensable tool for s...
research
09/17/2021

Level Sets or Gradient Lines? A Unifying View of Modal Clustering

The paper establishes a strong correspondence, if not an equivalence, be...

Please sign up or login with your details

Forgot password? Click here to reset