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Description
  • In the process of image analysis of complex systems consisting of large number of objects - typical for astronomy, thin film physics, biology, etc. - the reliable and accurate detection of both the size and spatial distribution of objects is very important. This contribution reviews the new approaches based on the neural network approach. The neural network approach is evaluated in terms of their performance and simplicity of their implementation. As a part of the development of the neural network approach a simple algorithm describing the spatial distribution of objects in the image is presented. While the new approach is tested on simulated hard-disk models, the results can be applied to the experimentally derived microphotographs of discontinuous and composite metal films.
  • In the process of image analysis of complex systems consisting of large number of objects - typical for astronomy, thin film physics, biology, etc. - the reliable and accurate detection of both the size and spatial distribution of objects is very important. This contribution reviews the new approaches based on the neural network approach. The neural network approach is evaluated in terms of their performance and simplicity of their implementation. As a part of the development of the neural network approach a simple algorithm describing the spatial distribution of objects in the image is presented. While the new approach is tested on simulated hard-disk models, the results can be applied to the experimentally derived microphotographs of discontinuous and composite metal films. (en)
Title
  • Neural network approach in image analysis of complex systems
  • Neural network approach in image analysis of complex systems (en)
skos:prefLabel
  • Neural network approach in image analysis of complex systems
  • Neural network approach in image analysis of complex systems (en)
skos:notation
  • RIV/44555601:13430/01:00001409!RIV/2002/MSM/134302/N
http://linked.open.../vavai/riv/strany
  • 223-227
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM 113200002), Z(MSM 134300001)
http://linked.open...iv/cisloPeriodika
  • 2-4
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 688653
http://linked.open...ai/riv/idVysledku
  • RIV/44555601:13430/01:00001409
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Neural network, thin film physics, image analysis. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • NL - Nizozemsko
http://linked.open...ontrolniKodProRIV
  • [50E808CA3685]
http://linked.open...i/riv/nazevZdroje
  • VACUUM
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...ocetUcastnikuAkce
http://linked.open...nichUcastnikuAkce
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 61
http://linked.open...iv/tvurceVysledku
  • Hrach, Rudolf
  • Malý, Marek
  • Novotný, Dušan
http://linked.open...n/vavai/riv/zamer
issn
  • 0042-207X
number of pages
http://localhost/t...ganizacniJednotka
  • 13430
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