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Review

2015

Review

2015

Euclidean distance matrices (EDMs) are matrices of the squared distances between points. The definition is deceivingly simple…

Review

2012

Review

2012

Euclidean distance geometry is the study of Euclidean geometry based on the concept of distance. This is useful in several…

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…

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…

Highly Cited

2004

Highly Cited

2004

Understanding the relationship among different distance measures is helpful in choosing a proper one for a particular application…

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…

Highly Cited

1999

Highly Cited

1999

Given a partial symmetric matrix A with only certain elements specified, the Euclidean distance matrix completion problem (EDMCP…

Highly Cited

1995

Highly Cited

1995

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

Highly Cited

1987

Highly Cited

1987

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

Highly Cited

1980