Discrepancy Directed Model Acquisition forAdaptive Perceptual

نویسندگان

  • Malini K. Bhandaru
  • Victor R. Lesser
چکیده

For complex perceptual tasks that are characterized by object occlusion and non-stationarity, recognition systems with adaptive signal processing front-ends have been developed. These systems rely on hand-crafted symbolic object models, which constitutes a knowledge acquisition bottleneck. We propose an approach to automate object model acquisition that relies on the detection and resolution of signal processing and interpretation discrepancies. The approach is applied to the task of acquiring acoustic-event models for the Sound Understanding Testbed (SUT).

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تاریخ انتشار 1998