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» A Riemannian approach to graph embedding
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TSMC
2010
12 years 11 months ago
Distance Approximating Dimension Reduction of Riemannian Manifolds
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Changyou Chen, Junping Zhang, Rudolf Fleischer
ISBI
2011
IEEE
12 years 8 months ago
Sparse Riemannian manifold clustering for HARDI segmentation
We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter fiber bundles. We cast thi...
Hasan Ertan Çetingül, René Vida...
CVPR
2007
IEEE
14 years 7 months ago
A Graph Cut Approach to Image Segmentation in Tensor Space
This paper proposes a novel method to apply the standard graph cut technique to segmenting multimodal tensor valued images. The Riemannian nature of the tensor space is explicitly...
Allen Tannenbaum, James G. Malcolm, Yogesh Rathi
ICPR
2010
IEEE
13 years 2 months ago
Rectifying Non-Euclidean Similarity Data Using Ricci Flow Embedding
Similarity based pattern recognition is concerned with the analysis of patterns that are specified in terms of object dissimilarity or proximity rather than ordinal values. For man...
Weiping Xu, Edwin R. Hancock, Richard C. Wilson
IDEAL
2005
Springer
13 years 10 months ago
Bearing Similarity Measures for Self-organizing Feature Maps
The neural representation of space in rats has inspired many navigation systems for robots. In particular, Self-Organizing (Feature) Maps (SOM) are often used to give a sense of lo...
Narongdech Keeratipranon, Frédéric M...