Multi-Stage Neural Supporting System for Time Domain Metal Detectors
S. Harneit, Matthias Reuter, Hadj Hamma Tadjine · 2006
In this work we propose an end-user supporting system for humanitarian demining tasks to semi-automatically classify signals of time domain metal detectors. Our multi-stage system consists of a first module to smooth the raw signals, followed by a neural feedforward net to classify the received signal's decay curve of the localized object at each sensor position. The resulting output activities of this net are accumulated to spatial vectors, which are propagated to a second feedforward net. Its resulting output activities are visualized in a 3D-end user interface and may be analyzed by different signal processing routines to be sensitive to changing soils and environmental conditions.