Towards a Tool for Visual Link Retrieval and Knowledge Discovery in Painting Datasets

  • Giovanna Castellano
  • Gennaro VessioEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1177)


This paper presents a preliminary investigation aimed at developing a tool for visual link retrieval and knowledge discovery in painting datasets. The proposed framework is based on a deep convolutional network to perform feature extraction and on a fully-unsupervised nearest neighbor approach to retrieve visual links among digitized paintings. Moreover, the proposed method makes it possible to study influences among artists by means of graph analysis. The tool is intended to help art historians better understand visual arts.


Cultural heritage Deep learning Computer Vision Visual link retrieval Knowledge discovery Paintings 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Dipartimento di InformaticaUniversità degli Studi di BariBariItaly

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