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CSIE
2009
IEEE
14 years 4 months ago
Evaluating Clustering Algorithms: Cluster Quality and Feature Selection in Content-Based Image Clustering
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Ward’s method, with the latter three being different hierarchical...
Mesfin Sileshi, Björn Gambäck
SIGIR
2003
ACM
14 years 3 months ago
ReCoM: reinforcement clustering of multi-type interrelated data objects
Most existing clustering algorithms cluster highly related data objects such as Web pages and Web users separately. The interrelation among different types of data objects is eith...
Jidong Wang, Hua-Jun Zeng, Zheng Chen, Hongjun Lu,...
ICIP
1999
IEEE
14 years 11 months ago
Unsupervised Low-Frequency Driven Segmentation of Color Images
This paper presents an algorithm for unsupervised segmentation of color images. The main idea behind it is the use of the low-frequency content of images which allows for smoothin...
Luca Lucchese, Sanjit K. Mitra
ICCV
2009
IEEE
1119views Computer Vision» more  ICCV 2009»
15 years 3 months ago
Spectral clustering of linear subspaces for motion segmentation
This paper studies automatic segmentation of multiple motions from tracked feature points through spectral embedding and clustering of linear subspaces. We show that the dimensi...
Fabien Lauer, Christoph Schn¨orr
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
14 years 10 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle