Heterogeneous sensor data fusion for target classification using adaptive distance function
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Publication:6602044
DOI10.1007/978-3-030-52406-7_1MaRDI QIDQ6602044
Orhan Karasakal, Bengü Atıcı, Esra Köktener Karasakal
Publication date: 11 September 2024
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- On the Dempster-Shafer framework and new combination rules
- The transferable belief model
- Support-vector networks
- A novel approach to information fusion in multi-source datasets: a granular computing viewpoint
- Conflicting information fusion based on an improved DS combination method
- Specification of training sets and the number of hidden neurons for multilayer perceptrons
- 10.1162/15324430260185646
- Interdependence between safety-control policy and multiple-sensor schemes via Dempster-Shafer theory
- Learning representations by back-propagating errors
- Upper and Lower Probabilities Induced by a Multivalued Mapping
- A logical calculus of the ideas immanent in nervous activity
- A simple decomposition method for support vector machines
- Convergence of a generalized SMO algorithm for SVM classifier design
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