Results 1 - 10 of 21,471

A Fast Marching Level Set Method for Monotonically Advancing Fronts

by J. A. Sethian - PROC. NAT. ACAD. SCI , 1995
"... We present a fast marching level set method for monotonically advancing fronts, which leads to an extremely fast scheme for solving the Eikonal equation. Level set methods are numerical techniques for computing the position of propagating fronts. They rely on an initial value partial differential eq ..."
Abstract - Cited by 630 (24 self) - Add to MetaCart
We present a fast marching level set method for monotonically advancing fronts, which leads to an extremely fast scheme for solving the Eikonal equation. Level set methods are numerical techniques for computing the position of propagating fronts. They rely on an initial value partial differential

Confidence-Based Segmentation of MR Imagery Using Region and Boundary Information with Nonlinear Scale-Space and Fast Marching Level Sets

by Jerod Weinman, George Bissias, Edward Riseman, Allen Hanson, Joseph Horowitz , 2003
"... Automatic segmentation of stroke lesions in magnetic resonance imagery is a difficult problem because anatomical knowledge is required for the most accurate decisions. Without such knowledge, classification rules seem inconsistent. We propose a hybrid boundary and region based segmentation model bui ..."
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built upon nonlinear scalespace and geometric active contours that captures the various segmentation rules necessary to segment lesions. After a user selects a point within damaged tissue and another point within healthy tissue, the image is examined at several levels of detail. At each such scale

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
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

Nonlinear total variation based noise removal algorithms

by Leonid I. Rudin, Stanley Osher, Emad Fatemi , 1992
"... A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using the g ..."
Abstract - Cited by 2271 (51 self) - Add to MetaCart
the gradient-projection method. This amounts to solving a time dependent partial differential equation on a manifold determined by the constraints. As t--- ~ 0o the solution converges to a steady state which is the denoised image. The numerical algorithm is simple and relatively fast. The results appear

A Fast Level Set Method for Propagating Interfaces

by David Adalsteinsson, James A. Sethian - JOURNAL OF COMPUTATIONAL PHYSICS , 1994
"... A method is introduced to decrease the computational labor of the standard level set method for propagating interfaces. The fast approach uses only points close to the curve at every time step. We describe this new algorithm and compare its efficiency and accuracy with the standard level set approac ..."
Abstract - Cited by 423 (28 self) - Add to MetaCart
A method is introduced to decrease the computational labor of the standard level set method for propagating interfaces. The fast approach uses only points close to the curve at every time step. We describe this new algorithm and compare its efficiency and accuracy with the standard level set

Mining Generalized Association Rules

by Ramakrishnan Srikant, Rakesh Agrawal , 1995
"... We introduce the problem of mining generalized association rules. Given a large database of transactions, where each transaction consists of a set of items, and a taxonomy (is-a hierarchy) on the items, we find associations between items at any level of the taxonomy. For example, given a taxonomy th ..."
Abstract - Cited by 591 (7 self) - Add to MetaCart
We introduce the problem of mining generalized association rules. Given a large database of transactions, where each transaction consists of a set of items, and a taxonomy (is-a hierarchy) on the items, we find associations between items at any level of the taxonomy. For example, given a taxonomy

Three-dimensional object recognition from single two-dimensional images

by David G. Lowe - Artificial Intelligence , 1987
"... A computer vision system has been implemented that can recognize threedimensional objects from unknown viewpoints in single gray-scale images. Unlike most other approaches, the recognition is accomplished without any attempt to reconstruct depth information bottom-up from the visual input. Instead, ..."
Abstract - Cited by 484 (7 self) - Add to MetaCart
. A high level of robustness in the presence of occlusion and missing data can be achieved through full application of a viewpoint consistency constraint. It is argued that similar mechanisms and constraints form the basis for recognition in human vision. This paper has been published in Artificial

Temperature-aware microarchitecture

by Kevin Skadron, Mircea R. Stan, Wei Huang, Sivakumar Velusamy, Karthik Sankaranarayanan, David Tarjan - In Proceedings of the 30th Annual International Symposium on Computer Architecture , 2003
"... With power density and hence cooling costs rising exponentially, processor packaging can no longer be designed for the worst case, and there is an urgent need for runtime processor-level techniques that can regulate operating temperature when the package’s capacity is exceeded. Evaluating such techn ..."
Abstract - Cited by 478 (52 self) - Add to MetaCart
With power density and hence cooling costs rising exponentially, processor packaging can no longer be designed for the worst case, and there is an urgent need for runtime processor-level techniques that can regulate operating temperature when the package’s capacity is exceeded. Evaluating

A simple distributed autonomous power control algorithm and its convergence

by Gerard J. Foschini, Zoran Miljanic - IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY , 1993
"... For wireless cellular communication systems, one seeks a simple effective means of power control of signals associated with randomly dispersed users that are reusing a single channel in different cells. By effecting the lowest interference environment, in meeting a required minimum signal-to-interf ..."
Abstract - Cited by 477 (3 self) - Add to MetaCart
power level of each of the signals, using only local measurements, so that eventually all users meet the p requirement. The local per channel power measurements include that of the intended signal as well as the undesired interference from other users (plus receiver noise). For a certain simple

CATH -- a hierarchic classification of protein domain structures

by C A Orengo, A D Michie, S Jones, D T Jones, M B Swindells, J M Thornton - STRUCTURE , 1997
"... Background: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structure-based classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function can ..."
Abstract - Cited by 470 (33 self) - Add to MetaCart
can also be assigned. The ever increasing number of known protein structures is too large to classify all proteins manually, therefore, automatic methods are needed for fast evaluation of protein structures. Results: We present a semi-automatic procedure for deriving a novel hierarchical
Results 1 - 10 of 21,471