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Similarity of Color Images

by Markus Stricker, Markus Orengo , 1995
"... We describe two new color indexing techniques. The first one is a more robust version of the commonly used color histogram indexing. In the index we store the cumulative color histograms. The L 1 -, L 2 -, or L1 -distance between two cumulative color histograms can be used to define a similarity mea ..."
Abstract - Cited by 495 (2 self) - Add to MetaCart
We describe two new color indexing techniques. The first one is a more robust version of the commonly used color histogram indexing. In the index we store the cumulative color histograms. The L 1 -, L 2 -, or L1 -distance between two cumulative color histograms can be used to define a similarity

Multimodality Image Registration by Maximization of Mutual Information

by Frederik Maes, André Collignon, Dirk Vandermeulen, Guy Marchal, Paul Suetens - IEEE TRANSACTIONS ON MEDICAL IMAGING , 1997
"... A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or in ..."
Abstract - Cited by 791 (10 self) - Add to MetaCart
A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence

Brain magnetic resonance imaging with contrast dependent on blood oxygenation.

by S Ogawa , T M Lee , A R Kay , D W Tank - Proc. Natl. Acad. Sci. USA , 1990
"... ABSTRACT Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high fields, we demonstrate in vivo images of brain microvasculature with imag ..."
Abstract - Cited by 648 (1 self) - Add to MetaCart
/cm (1 G = 0.1 mT). The slice width of the images shown was 500 ,4m and the in-plane pixel size was 117 ,um X Abbreviations: MRI, magnetic resonance imaging; BOLD, blood oxygenation level-dependent; EEG, electroencephalogram. 9868 The publication costs of this article were defrayed in part by page charge

Those who understand: Knowledge growth in teaching. Educational Researcher

by Lee S. Shulman , 1986
"... "He who can, does. He who cannot, teaches. “ 1 don't know in what fit of pique George Bernard Shaw wrote that infamous aphorism, words that have plagued members of the teach-ing profession for nearly a century. They are found in "Maxims for Revolutionists, " an appendix to his pl ..."
Abstract - Cited by 1369 (1 self) - Add to MetaCart
"He who can, does. He who cannot, teaches. “ 1 don't know in what fit of pique George Bernard Shaw wrote that infamous aphorism, words that have plagued members of the teach-ing profession for nearly a century. They are found in "Maxims for Revolutionists, " an appendix to his

Robust face recognition via sparse representation

by John Wright, Allen Y. Yang, Arvind Ganesh, S. Shankar Sastry, Yi Ma - IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2008
"... We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse signa ..."
Abstract - Cited by 936 (40 self) - Add to MetaCart
signal representation offers the key to addressing this problem. Based on a sparse representation computed by ℓ 1-minimization, we propose a general classification algorithm for (image-based) object recognition. This new framework provides new insights into two crucial issues in face recognition: feature

A fast learning algorithm for deep belief nets

by Geoffrey E. Hinton, Simon Osindero - Neural Computation , 2006
"... We show how to use “complementary priors ” to eliminate the explaining away effects that make inference difficult in densely-connected belief nets that have many hidden layers. Using complementary priors, we derive a fast, greedy algorithm that can learn deep, directed belief networks one layer at a ..."
Abstract - Cited by 970 (49 self) - Add to MetaCart
at a time, provided the top two layers form an undirected associative memory. The fast, greedy algorithm is used to initialize a slower learning procedure that fine-tunes the weights using a contrastive version of the wake-sleep algorithm. After fine-tuning, a network with three hidden layers forms a

Robust principal component analysis?

by Emmanuel J Candès , Xiaodong Li , Yi Ma , John Wright - Journal of the ACM, , 2011
"... Abstract This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component individually? We prove that under some suitable assumptions, it is possible to recover both the low-rank and the ..."
Abstract - Cited by 569 (26 self) - Add to MetaCart
-rank and the sparse components exactly by solving a very convenient convex program called Principal Component Pursuit; among all feasible decompositions, simply minimize a weighted combination of the nuclear norm and of the 1 norm. This suggests the possibility of a principled approach to robust principal component

Metaphors We Live By

by George Lakoff, Mark Johnson , 1980
"... 1. Make a list of some of the metaphors discussed by Lakoff and Johnson. Try inserting new words that convey a different meaning. For example, consider the expression, “I’d like to share some time with you ” rather than “spend some time with you.” 2. Make a list of “language asymmetries ” (see Part ..."
Abstract - Cited by 3387 (7 self) - Add to MetaCart
1. Make a list of some of the metaphors discussed by Lakoff and Johnson. Try inserting new words that convey a different meaning. For example, consider the expression, “I’d like to share some time with you ” rather than “spend some time with you.” 2. Make a list of “language asymmetries ” (see Part

MR Diffusion Tensor Spectroscopy and Imaging

by Peter J. Basser, James Mattiello, Denis LeBihan , 1994
"... This paper describes a new NMR imaging modality-MR diffusion tensor imaging. It consists of estimating an effective diffusion tensor, Deff, within a voxel, and then displaying useful quantities derived from it. We show how the phenomenon of anisotropic diffusion of water (or metabolites) in anisotro ..."
Abstract - Cited by 384 (11 self) - Add to MetaCart
new information within a macroscopic voxel that scalars (such as the apparent diffusivity, proton density, T1, and T2) do not.

Content-based image retrieval with relevance feedback

by Yong Rui, Thomas S. Huang, Sharad Mehrotra - in MARS. In Image Processing, 1997. Proceedings., International Conference on , 1997
"... Technology advances in the areas of Image processing (IP) and Information Retrieval (IR) have evolved separately for a long time. However, successful content-based image retrieval systems require the integration of the two. There is an urgent need to develop integration mechanisms to link the image ..."
Abstract - Cited by 331 (33 self) - Add to MetaCart
retrieval model to text retrieval model, such that the well established textretrieval techniques can be utilized. Approaches of converting image feature vectors (IP domain) to weighted-term vectors (IR domain) are proposed in this paper. Furthermore, the relevance feedback technique fromthe
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