Challenging deep image descriptors for retrieval in heterogeneous iconographic collections
Résumé
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
| Origine | Fichiers produits par l'(les) auteur(s) |
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