Control and explanation in a signal understanding environment

To interpret sensor signals like images, image sequences, or continuous speech the representation and use of task-specific knowledge is necessary. The paper presents a framework for the representation of declarative and procedural knowledge using a suitable definition of a semantic network. Based on that formalism a problem-independent control algorithm for the interpretation of sensor signals is presented. It provides both data-driven and model-driven control structures which can easily be combined to perform any mixed strategy. An explanation facility is available which makes the development of complex knowledge bases easier and increases the acceptance of such a knowledge-based analysis system.

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