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DAGSTUHL
2009
14 years 10 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
73
Voted
ISM
2005
IEEE
91views Multimedia» more  ISM 2005»
15 years 3 months ago
Research on the Discrimination of Pornographic and Bikini Images
Our research extends the general technologies detecting pornographic images to prevent the benign images whose content is approximate with the pornographic ones from being screene...
Yushi Wang, Weiqiang Wang, Wen Gao
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
14 years 11 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
FGR
2004
IEEE
167views Biometrics» more  FGR 2004»
15 years 1 months ago
Adaptive Learning of an Accurate Skin-Color Model
Due to variations of lighting conditions, camera hardware settings, and the range of skin coloration among human beings, a pre-defined skin-color model cannot accurately capture t...
Qiang Zhu, Kwang-Ting Cheng, Ching-Tung Wu, Yi-Leh...
SSPR
2010
Springer
14 years 8 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...