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ECCV
2010
Springer
15 years 3 months ago
Maximum Margin Distance Learning for Dynamic Texture Recognition
The range space of dynamic textures spans spatiotemporal phenomena that vary along three fundamental dimensions: spatial texture, spatial texture layout, and dynamics. By describin...
KAIS
2008
150views more  KAIS 2008»
14 years 9 months ago
A survey on algorithms for mining frequent itemsets over data streams
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
James Cheng, Yiping Ke, Wilfred Ng
71
Voted
MIR
2006
ACM
145views Multimedia» more  MIR 2006»
15 years 3 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
108
Voted
BMCBI
2008
214views more  BMCBI 2008»
14 years 8 months ago
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
Jukka Corander, Pekka Marttinen, Jukka Siré...
ICIP
2010
IEEE
14 years 7 months ago
Texture classification via patch-based sparse texton learning
Texture classification is a classical yet still active topic in computer vision and pattern recognition. Recently, several new texture classification approaches by modeling textur...
Jin Xie, Lei Zhang, Jane You, David Zhang