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Demonstration of an open source framework for qualitative evaluation of CBIR systems

Gomez, P.; Mohedano, E.; McGuinness, K.; Giro, X.; O'Connor, N.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
ACM Multimedia Conference 2018
Any de l'edició
Data de presentació
Llibre d'actes
Proceedings of 2018 ACM Multimedia Conference, Seoul, Republic of Korea, October 22-26, 2018 (MM’18)
Pàgina inicial
Pàgina final
DOI Obrir en finestra nova
Projecte finançador
Procesado de señales multimodales y aprendizaje automático en grafos.
Repositori Obrir en finestra nova Obrir en finestra nova
URL Obrir en finestra nova
Evaluating image retrieval systems in a quantitative way, for example by computing measures like mean average precision, allows for objective comparisons with a ground-truth. However, in cases where ground-truth is not available, the only alternative is to collect feedback from a user. Thus, qualitative assessments become important to better understand how the system works. Visualizing the results could be, in some scenarios, the only way to evaluate the results obtained and also the only opport...
Paraules clau
content-based image retrieval, deep learning, open source, retrieval, user interface, visual search
Grup de recerca
GPI - Grup de Processament d'Imatge i Vídeo
IDEAI-UPC Intelligent Data Science and Artificial Intelligence


  • Gomez Duran, Paula  (autor ponent)
  • Mohedano, Eva  (autor ponent)
  • McGuinness, Kevin  (autor ponent)
  • Giro Nieto, Xavier  (autor ponent)
  • O'Connor, Noel  (autor ponent)