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Object Recognition with Cluster MatchingLennartsson, Mattias January 2009 (has links)
<p>Within this thesis an algorithm for object recognition called Cluster Matching has been developed, implemented and evaluated. The image information is sampled at arbitrary sample points, instead of interest points, and local image features are extracted. These sample points are used as a compact representation of the image data and can quickly be searched for prior known objects. The algorithm is evaluated on a test set of images and the result is surprisingly reliable and time efficient.</p>
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Development of Computational Tools for Single-Cell DiscoveryDePasquale, Erica January 2020 (has links)
No description available.
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Object Recognition with Cluster MatchingLennartsson, Mattias January 2009 (has links)
Within this thesis an algorithm for object recognition called Cluster Matching has been developed, implemented and evaluated. The image information is sampled at arbitrary sample points, instead of interest points, and local image features are extracted. These sample points are used as a compact representation of the image data and can quickly be searched for prior known objects. The algorithm is evaluated on a test set of images and the result is surprisingly reliable and time efficient.
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