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Using Neural Networks to Detect Microfossil Teeth in Somosaguas Sur Paleontological Site

  • R. Gil-Pita
  • N. Sala-Burgos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4224)

Abstract

Automatic microfossil detection system allows to extract the position of the microfossils in a concentrate of mineral grains, speeding up the time required to analyze each sample. In this paper we study the use of Multilayer Perceptrons and Radial Basis Function Networks applied to the automatic microfossil teeth detection problem, focusing on the dependence of the performance with the size of the network, and with the size of the training set. The data used in the experiments are three images of concentrates with micromammal teeth from Somosaguas paleontological site, in Madrid (Spain). The obtained results demonstrate RBFNs perform better than MLPs in most of the considered cases, detecting most of the microfossil teeth in the images.

Keywords

Radial Basis Function Training Image Middle Miocene Radial Basis Function Network Hide Unit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • R. Gil-Pita
    • 1
    • 2
  • N. Sala-Burgos
    • 1
    • 2
  1. 1.Departamento de Teoría de la Señal y ComunicacionesUniversidad de AlcaláSpain
  2. 2.Departamento de PaleontologíaUniversidad Complutense de MadridSpain

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