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» Structured Learning and Prediction in Computer Vision
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FUZZIEEE
2007
IEEE
14 years 2 months ago
Mining and Predicting CpG islands
— A DNA sequence can be described as a string composed of four symbols: A, T, C and G. Each symbol represents a chemically distinct nucleotide molecule. Combinations of two nucle...
Christopher Previti, Oscar Harari, Coral del Val
CVPR
2007
IEEE
14 years 10 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
14 years 10 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...
ICIP
1999
IEEE
14 years 9 months ago
Video Sequence Learning and Recognition Via Dynamic Som
Information contained in the video sequences is crucial for an autonomous robot or a computer to learn and respond to its surrounding environment. In the past, robot vision is mai...
Qiong Liu, Yong Rui, Thomas S. Huang, Stephen E. L...
JMLR
2010
155views more  JMLR 2010»
13 years 6 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...