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ICASSP
2010
IEEE
15 years 5 months ago
Fast semi-supervised image segmentation by novelty selection
The goal of semi-supervised image segmentation is to obtain the segmentation from a partially labeled image. By utilizing the image manifold structure in labeled and unlabeled pix...
António R. C. Paiva, Tolga Tasdizen
CVPR
2007
IEEE
16 years 7 months ago
Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
ICCV
2005
IEEE
16 years 7 months ago
Neighborhood Preserving Embedding
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Xiaofei He, Deng Cai, Shuicheng Yan, HongJiang Zha...
ICML
2006
IEEE
16 years 5 months ago
Local distance preservation in the GP-LVM through back constraints
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
Joaquin Quiñonero Candela, Neil D. Lawrence
167
Voted
ICASSP
2010
IEEE
15 years 5 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi