paper-with-me

Papers

KL Divergence Based Agglomerative Clustering for Automated Vitiligo Grading

2015-06-01 · CVPR 2015 6 · Mithun Das Gupta, Srinidhi Srinivasa, Madhukara J., Meryl Antony

In this paper we present a symmetric KL divergence based agglomerative clustering framework to segment multiple levels of depigmentation in Vitiligo images. The proposed framework starts with a simple merge cost based on symmetric KL divergence. We extend the recent body of work related to Bregman divergence based agglomerative clustering and prove that the symmetric KL divergence is an upper-bound for uni-modal Gaussian distributions. This leads to a very simple yet elegant method for bottomup agglomerative clustering. We introduce albedo and reflectance fields as features for the distance computations. We compare against other established methods to bring out possible pros and cons of the proposed method.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Clustering

Similar Papers 제목 키워드 기반

MultiDendrograms: Variable-Group Agglomerative Hierarchical Clusterings

2012-01-08 · Sergio Gomez, Justo Montiel, David Torres, Alberto Fernandez

MultiDendrograms is a Java-written application that computes agglomerative hierarchical clusterings of data. Starting from a distances (or weights) matrix, MultiDendrograms is able to calculate its dendrograms using the …

Clustering

Analysis of Agglomerative Clustering

2010-12-16 · Marcel R. Ackermann, Johannes Blömer, Daniel Kuntze, Christian Sohler

The diameter $k$-clustering problem is the problem of partitioning a finite subset of $\mathbb{R}^d$ into $k$ subsets called clusters such that the maximum diameter of the clusters is minimized. One early clustering algo…

Clustering

Robust Hierarchical Clustering

2014-01-01 · Maria-Florina Balcan, YIngyu Liang, Pramod Gupta

One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across many different fields ranging from computational biology to social sciences to computer v…

Clustering

Agglomerative Info-Clustering

2017-01-18 · Chung Chan, Ali Al-Bashabsheh, Qiaoqiao Zhou

An agglomerative clustering of random variables is proposed, where clusters of random variables sharing the maximum amount of multivariate mutual information are merged successively to form larger clusters. Compared to t…

Clustering

Uncertainty-Aware Domain Adaptation for Vitiligo Segmentation in Clinical Photographs

2025-12-12 · Wentao Jiang, Vamsi Varra, Caitlin Perez-Stable, Harrison Zhu 외 arxiv

Accurately quantifying vitiligo extent in routine clinical photographs is crucial for longitudinal monitoring of treatment response. We propose a trustworthy, frequency-aware segmentation framework built on three synergi…

Domain Adaptation