Ev ve Ofis taşıma sektöründe lider olmak.Teknolojiyi takip ederek bunu müşteri menuniyeti amacı için kullanmak.Sektörde marka olmak.
İstanbul evden eve nakliyat
Misyonumuz sayesinde edindiğimiz müşteri memnuniyeti ve güven ile müşterilerimizin bizi tavsiye etmelerini sağlamak.
Increasing
the discrimination of SAR recognition models
Presented by: Grinnell Jones
ABSTRACT: The focus of this talk is optimizing recognition
models for Synthetic Aperture Radar (SAR) signatures of vehicles
to improve the performance of a recognition algorithm under
the extended operating conditions of target articulation,
occlusion and configuration variants. The recognition models
are based on quasi-invariant local features: scattering center
locations and magnitudes. The approach determines the similarities
and differences among the various vehicle models. Methods
to penalize similar features or reward dissimilar features
are used to increase the distinguishability of the recognition
model instances.
Extensive experimental recognition results are presented in
terms of confusion matricies and reciever operating characteristic
(ROC) curves to show ther improvements in recognition performance
for MSTAR vehicle targets with articulation, configuration
variants and occlusion.
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