141 search results - page 20 / 29 » Unsupervised Image Classification with a Hierarchical EM Alg... |
ISBI
2006
IEEE
2006
IEEE
Mixture principal component analysis for distribution volume parametric imaging in brain PET studies
14 years 8 months ago
In this paper, we present a mixture Principal Component Analysis (mPCA)-based approach for voxel level quantification of dynamic positron emission tomography (PET) data in brain s...
ICIAP
2003
ACM
14 years 25 days ago
2003
ACM
Principal component analyses (PCA) has been widely used in reduction of the dimensionality of datasets, classification, feature extraction, etc. It has been combined with many oth...
NIPS
2008
13 years 9 months ago
2008
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
CVPR
2010
IEEE
14 years 4 months ago
2010
IEEE
In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...