Suche nach „[V.] [Hofmann]“ hat 5 Publikationen gefunden
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    DigitalS: TC Freyung

    Beitrag (Sammelband oder Tagungsband)

    Peter Hofmann, V. Andrejchenko, P. Lettmayer, M. Schmitzberger, M. Gruber, I. Ozan, M. Belgiu, R. Graf, T. Lampoltshammer, S. Wegenkittl

    Agent based image analysis (ABIA)-preliminary research results from an implemented framework

    Proceedings of GEOBIA 2016: Solutions and Synergies (Enschede, Netherlands; September 14-16, 2016)


    DigitalS: TC Freyung


    Peter Hofmann, P. Lettmayer, T. Blaschke, M. Belgiu, S. Wegenkittl, R. Graf, T. Lampoltshammer, V. Andrejchenko

    Towards a framework for agent-based image analysis of remote-sensing data

    International Journal of Image and Data Fusion, vol. 6, no. 2, pp. 115-137


    DOI: 10.1080/19479832.2015.1015459

    Abstract anzeigen

    Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

    S: TC Freyung


    Peter Hofmann, P. Lettmayer, T. Blaschke, M. Belgiu, S. Wegenkittl, R. Graf, T. Lampoltshammer, V. Andrejchenko

    ABIA – A Conceptual Framework for Agent Based Image Analysis

    South-Eastern European Journal of Earth Observation and Geomatics, vol. 3, no. 2S, pp. 125-130


    F: Maschinenbau und Mechatronik

    Beitrag (Sammelband oder Tagungsband)

    D. Fisch, A. Hofmann, V. Hornik, I. Dedinski, Bernhard Sick

    A Framework for Large-Scale Simulation of Collaborative Intrusion Detection

    Proceedings of the IEEE Conference on Soft Computing in Industrial Applications (SMCia/08); Muroran, Japan; 25.-27.06.2008


    I: Zentrum für Akademische Weiterbildung

    Beitrag (Sammelband oder Tagungsband)

    Andreas Gegenfurtner, K. Hies, V. Hofmann, G. Jahn, F. Lehner, J. Mattern, A. Nikitopoulos

    Fehlerkultur [Error culture]

    Mitarbeiterqualifizierung und -mobilität: Einflussfaktoren und Auswirkungen des flexiblen Mitarbeitereinsatzes im logistischen Umfeld, Regensburg