Characterization of the Performance of Memetic Algorithms for the Automation of Bone Tracking With Fluoroscopy-Reference-Cited by-同舟云学术

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Characterization of the Performance of Memetic Algorithms for the Automation of Bone Tracking With Fluoroscopy

Published:2015-02 Issue:1 Volume:19 Page:19-30
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Tersi Luca,Fantozzi Silvia,Stagni Rita

Funder

PRIN

Program POR-FESR 2007–2013, Asse 1, Attività I1.1, Emilia Romagna region, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/7024198/06697879.pdf?arnumber=6697879

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3. Self-adaptive learning for hybrid genetic algorithms;Evolutionary Intelligence;2020-05-25

4. Toward Efficient Design Space Exploration for Fault-Tolerant Multiprocessor Systems;IEEE Transactions on Evolutionary Computation;2020-02

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