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Automatic design of pulse coupled neurons for image segmentation
KTH, Skolan för teknikvetenskap (SCI), Fysik, Partikel- och astropartikelfysik.
2008 (engelsk)Inngår i: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 71, nr 10-12, s. 1980-1993Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Automatic Design of Algorithms through Evolution (ADATE) is a program synthesis system that creates recursive programs in a functional language with automatic invention of recursive help functions and self-adaptive optimization of numerical values. We implement a neuron in a pulse coupled neural network (PCNN) as a recursive function in the ADATE language and then use ADATE to automatically evolve better PCNN neurons for image segmentation. Our technique is generally applicable for automatic improvement of most image processing algorithms and neural computing methods. It may be used either to generally improve a given implementation or to tailor that implementation to a specific problem, which with respect to image segmentation for example can be road following for autonomous vehicles or infrared image segmentation for heat seeking missiles that are to distinguish the heat source of the target from flares.

sted, utgiver, år, opplag, sider
2008. Vol. 71, nr 10-12, s. 1980-1993
Emneord [en]
image segmentation, pulse coupled neural networks, automatic, programming, ADATE, neural-networks, edge-detection, cuts
Identifikatorer
URN: urn:nbn:se:kth:diva-17672DOI: 10.1016/j.neucom.2007.10.018ISI: 000257413300022Scopus ID: 2-s2.0-44649200506OAI: oai:DiVA.org:kth-17672DiVA, id: diva2:335717
Merknad
QC 20100525Tilgjengelig fra: 2010-08-05 Laget: 2010-08-05 Sist oppdatert: 2017-12-12bibliografisk kontrollert

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