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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Tadjine, H.H. Reuter, M. Harneit, S. |
| Copyright Year | 2005 |
| Description | Author affiliation: CUTEC Inst. GmbH, Clausthal (Tadjine, H.H.; Reuter, M.; Harneit, S.) |
| Abstract | 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 |
| Starting Page | 145 |
| Ending Page | 150 |
| File Size | 1371748 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780395212 |
| DOI | 10.1109/ICTTA.2006.1684360 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-04-24 |
| Publisher Place | Syria |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Temperature sensors Landmine detection Layout Neurons Object detection Detectors Thermal conductivity Feature extraction Electrical capacitance tomography Buried object detection |
| Content Type | Text |
| Resource Type | Article |
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