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Radar Recognition Based on SIFT Descriptor

Authors: Xinming Liu;

Radar Recognition Based on SIFT Descriptor

Abstract

Radar recognition is an important task in many flelds. The diversity of image sources requires the recognition be invariant to many kinds of image transformations. SIFT is proved to be the best local descriptor in achieving invariance. According to the fraction of keypoints that are matched to the reference image, two thresholds are set to provide more accurate recognition. A soft decision with a confldence degree is provided to satisfy various demands for difierent accuracy. Experiments show that SIFT achieves good invariance to scale, brightness, rotation and slight a‐ne transformations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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