Multimedia Information Retrieval (AIMIR) research group is part of the NeMIS laboratory of the Information Science and Technologies Institute "A. Faedo" (ISTI) of the Italian National Research Council (CNR). The AIMIR group has a long experience in topics related to: Artificial Intelligence, Multimedia Information Retrieval, Computer Vision and Similarity search on a large scale. We aim at investigating the use of Artificial Intelligence and Deep Learning, for Multimedia Information Retrieval, addressing both effectiveness and efficiency. Multimedia information retrieval techniques should be able to provide users with pertinent results, fast, on huge amount of multimedia data. Application areas of our research results range from cultural heritage to smart tourism, from security to smart cities, from mobile visual search to augmented reality. This report summarize the 2019 activities of the research group.

AIMIR 2019 Research Activities

Amato G;Bolettieri P;Carrara F;Ciampi L;Di Benedetto M;Debole F;Falchi F;Gennaro C;Lagani G;Massoli FV;Messina N;Rabitti F;Savino P;Vadicamo L;Vairo C
2019

Abstract

Multimedia Information Retrieval (AIMIR) research group is part of the NeMIS laboratory of the Information Science and Technologies Institute "A. Faedo" (ISTI) of the Italian National Research Council (CNR). The AIMIR group has a long experience in topics related to: Artificial Intelligence, Multimedia Information Retrieval, Computer Vision and Similarity search on a large scale. We aim at investigating the use of Artificial Intelligence and Deep Learning, for Multimedia Information Retrieval, addressing both effectiveness and efficiency. Multimedia information retrieval techniques should be able to provide users with pertinent results, fast, on huge amount of multimedia data. Application areas of our research results range from cultural heritage to smart tourism, from security to smart cities, from mobile visual search to augmented reality. This report summarize the 2019 activities of the research group.
2019
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Artificial Intelligence
Computer Vision
Multimedia Information Retrieval
Similarity Search
Hebbian Learning
Relational Learning
Face Recognition
Learning in Virtual Worlds
File in questo prodotto:
File Dimensione Formato  
prod_413891-doc_145792.pdf

accesso aperto

Descrizione: Annual report
Dimensione 6.25 MB
Formato Adobe PDF
6.25 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/367246
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact