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Parameter-orientated segmentation algorithm evaluation

Al-Muhairi, H and Fleury, M and Clark, AF (2011) Parameter-orientated segmentation algorithm evaluation. In: UNSPECIFIED, ? - ?.

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Quantitative testing of segmentation algorithms implies rigorous testing against ground-truth segmentations. Though under-reported in the literature, the performance of a segmentation algorithm depends on the choice of input parameters across core, pre- and post-processing stages. The paper highlights the importance of post-processing parameters when the figure of merit is the Berkeley F-measure. It also shows that the search of a parameter space with a genetic algorithm is not only accelerated through the inclusion of a time factor in the cost function but the relative importance of different parameters is highlighted. © 2011 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2011 IEEE GCC Conference and Exhibition, GCC 2011
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Clare Chatfield
Date Deposited: 15 Jul 2015 15:58
Last Modified: 05 Feb 2019 19:15

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