Intelli ent system for the detection of buried ob ects based on hu-Stu tures usin metal detector

Hybrid classification structures of buried object in different soils using time domain metal detectors are presented in this paper. This approach consists of self organising memories and backpropagation nets combined with the inter-neural whu-structures, whereby special pre-processing methods like DLS and fitting-methods are used to extract the feature specific items. In this work, an end-user supporting system for humanitarian demining tasks to semiautomatic ally classify signals is also proposed. In addition these structures enable to integrate several aspects of a scene into a mega-concept corresponding to the chunking process of the brain. The categorization of concepts will hereby be done by active whu-structures which become dominant since they sum up the activities of the involved neurons instead of considering one and only one high-active winner neuron. Using the proposed method, results confirm, that the presence of buried objects in land-mine could be localized and some of them classified