Use of artificial neural networks on optical track width measurements

Richard J. Smith, Chung W. See, Michael Geoffrey Somekh, Andrew Yacoot

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

We have demonstrated recently that, by using an ultrastable optical interferometer together with artificial neural networks (ANNs), track widths down to 60 nm can be measured with a 0.3 NA objective lens. We investigate the effective conditions for training ANNs. Experimental results will be used to show the characteristics of the training samples and the data format of the ANN inputs required to produce suitably trained ANNs. Results obtained with networks measuring double tracks, and classifying different structures, will be presented to illustrate the capability of the technique. We include a discussion on expansion of the application areas of the system, allowing it to be used as a general purpose instrument.
Original languageEnglish
Pages (from-to)4857-4866
Number of pages10
JournalApplied Optics
Volume46
Issue number22
DOIs
Publication statusPublished - 1 Aug 2007
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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