Abstract
The acquisition and the application of image categories are basic operations underlying the organization of human knowledge. Most traditional classification-learning paradigms reduce the learning process to a search for appropriate combinations of given, well-defined features. By contrast, the formation of image categories, for instance in medical diagnostics, is often characterised by a lack of knowledge concerning the relevant feature dimensions. Thus, the acquisition of unfamiliar complex images involves a specific perceptive component, i.e. feature analysis becomes part of the learning process. To describe human categorization performance we have developed a probabilistic Bayesian model where mental image categories are represented by virtual prototypes. We show that this approach not only allows for the description of visual field effects on the generation of image categories. It also permits to analyze the dynamics of the learning process. The resulting learning tomograms suggest that category learning of images is an integrative visual-cognitive task involving both processes of perceptual feature formation and hypothesis testing.
Zusammenfassung
Der Erwerb und das Anwenden bildkategorialer Konzepte gelten als kognitive Grundoperationen bei der Organisation menschlichen Wissens. Klassische Paradigmen zum Klassifikationslernen reduzieren den Lernvorgang zumeist auf die Entdeckung einer geeigneten Kombinatorik für bestimmte vorgegebene Merkmale. Demgegen- über sind Entscheidungsituationen des bildkategorialen Lernens, etwa im Bereich der medizinischen Diagnostik, häufig dadurch gekennzeichnet, daß die relevanten Reizdimensionen a priori unbekannt sind. Klassifikationslernen von unvertrautem, komplexem Bildmaterial weist somit eine spezifisch perzeptive Komponente auf, d.h. die Merkmalsanalyse wird Teil des eigentlichen Lernvorgangs. Zur Beschreibung bildkategorialer Sehleistungen haben wir ein probabilistisches Bayes-Modell entwickelt, bei dem mentale Kategorien durch virtuelle Prototypen repräsentiert sind. Wir zeigen, daß dieser Ansatz nicht nur die Darstellung des Einflusses von Gesichtsfeldeffekten auf den Aufbau mentaler Bildkategorien ermöglicht, sondern auch die Analyse ihrer Dynamik während des Lernprozesses. Die hieraus resultierenden Lerntomogramme erweisen, daß bildkategoriales Lernen eine visuell-kognitive Leistung darstellt. Sie umfaßt gleichermaßen Prozesse der perzeptiven Merkmalskonstitution wie der induktiven Hypothesenbildung.
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Diese Arbeit wurde von der Deutschen Forschungsgemeinschaft (Ju 230/5-1, Re 337/10-2) gefördert
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Jüttner, M., Rentschler, I. Bildkategoriales Lernen. Kognit. Wiss. 9, 103–113 (2001). https://doi.org/10.1007/BF03354943
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DOI: https://doi.org/10.1007/BF03354943