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Similarity searches in face databases

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2009) 5716 LNCS 443-450
DOI: 10.1007/978-3-642-04146-4_48
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Abstract

In this paper the problem of similarity searches in face databases is addressed. An approach based on relevance feedback is proposed to iteratively improve the query result. The approach is suitable both to supervised and unsupervised contexts. The efficacy of the learning procedures are confirmed by the results obtained on publicly available databases of faces. © 2009 Springer Berlin Heidelberg.

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Franco, A., & Maio, D. (2009). Similarity searches in face databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5716 LNCS, pp. 443–450). https://doi.org/10.1007/978-3-642-04146-4_48

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