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Swarm optimised few-view binary tomography

Swarm optimised few-view binary tomography

Al-Rifaie, Mohammad Majid ORCID: 0000-0002-1798-9615 and Blackwell, Tim (2022) Swarm optimised few-view binary tomography. In: Applications of Evolutionary Computation 25th European Conference, EvoApplications 2022. Lecture Notes in Computer Science, 13224 . Springer, pp. 30-45. ISBN 978-3031024610 ISSN 0302-9743 (Print), 1611-3349 (Online) (doi:https://doi.org/10.1007/978-3-031-02462-7_3)

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Abstract

This paper considers a swarm optimisation approach to few-view tomographic reconstruction. DFOMAX, a high diversity swarm optimiser, demonstrably reconstructs binary images to a high fidelity, outperforming a leading algebraic technique, differential evolution and particle swarm optimisation on four standard phantoms. The paper considers the effectiveness of optimisers that have been developed for optimal low dimensional performance and concludes that trial solution clamping on the walls of the feasible search space is important for good performance.

Item Type: Conference Proceedings
Title of Proceedings: Applications of Evolutionary Computation 25th European Conference, EvoApplications 2022
Uncontrolled Keywords: swarm optimisation, binary tomography, high dimensional optimisation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified: 04 May 2022 10:11
URI: http://gala.gre.ac.uk/id/eprint/35940

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