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DAGM
2010
Springer
13 years 6 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
ISBI
2004
IEEE
14 years 6 months ago
A Probabilistic Framework for the Detection and Tracking in Time of Multiple Sclerosis Lesions
A novel statistical scheme for the automatic detection and tracking in time of relapsing-remitting multiple sclerosis (MS) lesions in image sequences is described. Coherent space-...
Allon Shahar, Hayit Greenspan
AVSS
2007
IEEE
13 years 11 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen
ICIAR
2010
Springer
13 years 2 months ago
Image Segmentation for Robots: Fast Self-adapting Gaussian Mixture Model
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
Nicola Greggio, Alexandre Bernardino, José ...
DIAL
2006
IEEE
129views Image Analysis» more  DIAL 2006»
13 years 9 months ago
Ink recognition based on statistical classification methods
Statistical classification methods can be applied on images of historical manuscript in order to characterize the various kinds of inks used. As these methods do not require destr...
Vasiliki Kokla, Alexandra Psarrou, Vassilis Konsta...