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2018 24th International Conference on Pattern Recognition (ICPR), 2018
In this paper, we present a novel distance metric called Segmentation Edit Distance (SED) and its use as a segmentation evaluation metric. In segmentation evaluation, the difference or distance of a test segmentation and the associated ground truth segmentation are measured in order to compare different algorithms.
Daniel Pucher, Walter G. Kropatsch
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In this paper, we present a novel distance metric called Segmentation Edit Distance (SED) and its use as a segmentation evaluation metric. In segmentation evaluation, the difference or distance of a test segmentation and the associated ground truth segmentation are measured in order to compare different algorithms.
Daniel Pucher, Walter G. Kropatsch
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Swap and mismatch edit distance
Algorithmica, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Amihood Amir +2 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004
Edit distance was originally developed by Levenstein several decades ago to measure the distance between two strings. It was found that this distance can be computed by an elegant dynamic programming procedure. The edit distance has played important roles in a wide array of applications due to its representational efficacy and computational efficiency.
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Edit distance was originally developed by Levenstein several decades ago to measure the distance between two strings. It was found that this distance can be computed by an elegant dynamic programming procedure. The edit distance has played important roles in a wide array of applications due to its representational efficacy and computational efficiency.
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Collaborative editing at a distance
IPCC 98. Contemporary Renaissance: Changing the Way we Communicate. Proceedings 1998 IEEE International Professional Communication Conference (Cat. No.98CH36332), 2002Twenty years ago, to edit journal manuscripts was a slow, time-consuming process. The articles had to be retyped following each change and, if the authors and editors lived in different towns or countries, they had to be mailed between the author, production editor, and language editor.
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Biological Network Edit Distance
Journal of Computational Biology, 2016Interactions among biological entities contain more information than purely the similarities between the entities. For example, interactions between genes, and gene products, can be more informative than the sequence similarities of the genes involved.
Martin McGrane, Michael A. Charleston
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A relation between edit distance for ordered trees and edit distance for Euler strings
Information Processing Letters, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tatsuya Akutsu
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A survey of graph edit distance
Pattern Analysis and Applications, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xinbo Gao 0001 +3 more
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Normalizing the weighted edit distance
Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5), 2002In this paper, we discuss the weighted edit distance and two well known normalizations, one based on editing path lengths and one based on the string lengths. We investigate the limitations of these approaches as well as the restrictions on the associated weight function including the triangular inequality. As a solution to the problems pointed out, we
Achim Weigel, Frank Fein
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Homomorphic Computation of Edit Distance
2015These days genomic sequence analysis provides a key way of understanding the biology of an organism. However, since these sequences contain much private information, it can be very dangerous to reveal any part of them. It is desirable to protect this sensitive information when performing sequence analysis in public.
Jung Hee Cheon +2 more
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2015
In pattern recognition and data mining applications, where the underlying data is characterized by complex structural relationships, graphs are often used as a formalism for object representation. Yet, the high representational power and flexibility of graphs is accompanied by a significant increase of the complexity of many algorithms.
Kaspar Riesen +3 more
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In pattern recognition and data mining applications, where the underlying data is characterized by complex structural relationships, graphs are often used as a formalism for object representation. Yet, the high representational power and flexibility of graphs is accompanied by a significant increase of the complexity of many algorithms.
Kaspar Riesen +3 more
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