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Review

2016

Review

2016

This is an expository paper on the theory of gradient flows, and in particular of those PDEs which can be interpreted as gradient… Expand

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Review

2016

Review

2016

In this paper, we tackle the issue of clustering trajectories of geolocalized observations based on the distance between… Expand

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Highly Cited

2009

Highly Cited

2009

Common visual codebook generation methods used in a Bag of Visual words model, e.g. k-means or Gaussian Mixture Model, use the… Expand

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Highly Cited

2004

Highly Cited

2004

Optimization is the science of making a best choice in the face of conflicting requirements. Any convex optimization problem has… Expand

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Highly Cited

2004

Highly Cited

2004

The robustness of quantitative measures of compositional dissimilarity between sites was evaluated using extensive computer… Expand

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Highly Cited

2003

Highly Cited

2003

A sequential algorithm is presented for computing the exact Euclidean distance transform (DT) of a k-dimensional binary image in… Expand

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Highly Cited

1997

Highly Cited

1997

Instance-based learning techniques typically handle continuous and linear input values well, but often do not handle nominal… Expand

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Highly Cited

1995

Highly Cited

1995

Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a two-dimensional… Expand

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Highly Cited

1994

Highly Cited

1994

Abstract In this paper, we propose a new method to obtain the Euclidean distance transformation and the Voronoi diagram based on… Expand

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Highly Cited

1980

Highly Cited

1980

Based on a two-component descriptor, a distance label for each point, it is shown that Euclidean distance maps can be generated… Expand

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