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Challenging deep image descriptors for retrieval in heterogeneous iconographic collections

2019-09-19 08:54:51
Dimitri Gominski (LaSTIG), Martyna Poreba (LaSTIG), Valérie Gouet-Brunet (LaSTIG), Liming Chen (LaSTIG)
arXiv_CV
     
Abstract

This article proposes to study the behavior of recent and efficient state-of-the-art deep-learning based image descriptors for content-based image retrieval, facing a panel of complex variations appearing in heterogeneous image datasets, in particular in cultural collections that may involve multi-source, multi-date and multi-view Permission to make digital

Abstract (translated)

URL

https://arxiv.org/abs/1909.08866

PDF

https://arxiv.org/pdf/1909.08866.pdf

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