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Inductive Learning Methods in the Simple Image Understanding System

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Computer Vision and Graphics (ICCVG 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6374))

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Abstract

This article presents a proposition of using inductive learning methods in the task of creating the knowledge base for an image understanding system. With the help of the evolutionary algorithm, it is possible to synthesize an optimized system with the hierarchical structure of knowledge. The paper points to the key problem of the whole method - the creation of an effective algorithm of conceptual clustering. Some possible solutions are discussed.

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References

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Pedagogical University of Cracow, ul.Podchora̧żych 2, 30-084, Kraków, Poland

    Krzysztof Wójcik

Authors
  1. Krzysztof Wójcik
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Editor information

Editors and Affiliations

  1. Polish-Japanese Institute of Information Technology, 86 Koszykowa St, 02-008, Warsaw, Poland

    Leonard Bolc

  2. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Faculty of Applied Informatics and Mathematics, Department of Informatics, Warsaw University of Life Sciences, Nowoursynowska 159, 02-776, Warsaw, Poland

    Leszek J. Chmielewski

  4. Polish-Japanese Institute of Information Technology, 86 Koszykowa St, 02-008 Warsaw, konradw@pjwstk.edu.pl, The Silesian University of Technology, Institute of Computer Science, Akademicka 16, 44-100 Gliwice, Polan

    Konrad Wojciechowski

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Wójcik, K. (2010). Inductive Learning Methods in the Simple Image Understanding System. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15910-7_11

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  • DOI: https://doi.org/10.1007/978-3-642-15910-7_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15909-1

  • Online ISBN: 978-3-642-15910-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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