On the analysis of neural networks for image processing

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    Abstract

    This paper illustrates a novel method to analyze artificial neural networks so as to gain insight into their internal functionality. To this purpose, we will show analysis results of some feed-forward–error-back-propagation neural networks for image processing. We will describe them in terms of domain-dependent basic functions, which are, in the case of the digital image processing domain, differential operators of various orders and with various angles of operation. Some other pixel classification techniques are analyzed in the same way, enabling easy comparison.
    Original languageUndefined
    Title of host publicationProceedings of KES2003 vol. II
    EditorsVasile Palade, Robert J. Howlett, Lakhmi Jain
    Place of PublicationOxford, UK
    PublisherSpringer
    Pages950-957
    Number of pages8
    ISBN (Print)3-540-40804-5
    DOIs
    Publication statusPublished - Sep 2003

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer
    Volume2774

    Keywords

    • IR-45400
    • METIS-212150
    • EWI-9667

    Cite this

    van der Zwaag, B. J., Slump, C. H., & Spaanenburg, L. (2003). On the analysis of neural networks for image processing. In V. Palade, R. J. Howlett, & L. Jain (Eds.), Proceedings of KES2003 vol. II (pp. 950-957). (Lecture Notes in Computer Science; Vol. 2774). Oxford, UK: Springer. https://doi.org/10.1007/978-3-540-45226-3_130, https://doi.org/10.1007/b12003