Anatomical parts-based regression using non-negative matrix factorization
暂无分享,去创建一个
B. S. Manjunath | Kent A. Kiehl | Scott T. Grafton | Swapna Joshi | Shanmugavadivel Karthikeyan | K. Kiehl | Swapna Joshi | S. Karthikeyan
[1] Mark W. Woolrich,et al. Bayesian analysis of neuroimaging data in FSL , 2009, NeuroImage.
[2] Karl J. Friston,et al. Voxel-Based Morphometry—The Methods , 2000, NeuroImage.
[3] R. Kikinis,et al. Age-related changes in intracranial compartment volumes in normal adults assessed by magnetic resonance imaging. , 1996, Journal of neurosurgery.
[4] R. Kikinis,et al. White matter changes with normal aging , 1998, Neurology.
[5] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[6] Stan Z. Li,et al. Learning representative local features for face detection , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[7] Michael Lindenbaum,et al. Nonnegative Matrix Factorization with Earth Mover's Distance Metric for Image Analysis , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Yunde Jia,et al. FISHER NON-NEGATIVE MATRIX FACTORIZATION FOR LEARNING LOCAL FEATURES , 2004 .
[9] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[10] W. Härdle. Applied Nonparametric Regression , 1992 .
[11] Bruce A. Draper,et al. PCA vs. ICA: A Comparison on the FERET Data Set , 2002, JCIS.
[12] Mark W. Woolrich,et al. Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.
[13] Patrik O. Hoyer,et al. Non-negative Matrix Factorization with Sparseness Constraints , 2004, J. Mach. Learn. Res..
[14] Guido Gerig,et al. Effects of Healthy Aging Measured By Intracranial Compartment Volumes Using a Designed MR Brain Database , 2005, MICCAI.
[15] Terrence J. Sejnowski,et al. The “independent components” of natural scenes are edge filters , 1997, Vision Research.
[16] Dietrich Lehmann,et al. Nonsmooth nonnegative matrix factorization (nsNMF) , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] P. Thomas Fletcher,et al. Population Shape Regression from Random Design Data , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[18] Christos Davatzikos,et al. Voxel-Based Morphometry Using the RAVENS Maps: Methods and Validation Using Simulated Longitudinal Atrophy , 2001, NeuroImage.
[19] Christoph Schnörr,et al. Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming , 2006, J. Mach. Learn. Res..
[20] H. Sebastian Seung,et al. Learning the parts of objects by non-negative matrix factorization , 1999, Nature.
[21] M. Turk,et al. Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.
[22] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[23] Ker-Chau Li,et al. On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma , 1992 .
[24] S. Palmer. Hierarchical structure in perceptual representation , 1977, Cognitive Psychology.
[25] Michael Lindenbaum,et al. Nonnegative Matrix Factorization with Earth Mover's Distance metric , 2009, CVPR.
[26] Ker-Chau Li,et al. Sliced Inverse Regression for Dimension Reduction , 1991 .
[27] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[28] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[29] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[30] Stan Z. Li,et al. Learning spatially localized, parts-based representation , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[31] Pierre Comon. Independent component analysis - a new concept? signal processing , 1994 .