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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 11 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICIP
2004
IEEE
14 years 9 months ago
Discovering meaningful multimedia patterns with audio-visual concepts and associated text
The work presents the first effort to automatically annotate the semantic meanings of temporal video patterns obtained through unsupervised discovery processes. This problem is in...
Lexing Xie, Lyndon S. Kennedy, Shih-Fu Chang, Ajay...
ICCBR
2007
Springer
14 years 1 months ago
From Anomaly Reports to Cases
Abstract. Creating case representations in unsupervised textual case-based reasoning applications is a challenging task because class knowledge is not available to aid selection of...
Stewart Massie, Nirmalie Wiratunga, Susan Craw, Al...
ICMCS
2006
IEEE
181views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Toward Intelligent Use of Semantic Information on Subspace Discovery for Image Retrieval
Image retrieval has been widely used in many fields of science and engineering. The semantic concept of user interest is obtained by a learning process. Traditional techniques oft...
Jie Yu, Qi Tian
AUSAI
2006
Springer
13 years 11 months ago
Clustering Similarity Comparison Using Density Profiles
The unsupervised nature of cluster analysis means that objects can be clustered in many different ways. This means that different clustering algorithms can lead to vastly different...
Eric Bae, James Bailey, Guozhu Dong