Multi-Query Image Retrieval Based on Deep Learning and Pareto Optimality Derin Ogrenme ve Pareto Eniyileme Tabanli Cok Sorgulu Goruntu Erisimi

VURAL C., Akbacak E.

28th Signal Processing and Communications Applications Conference, SIU 2020, Gaziantep, Türkiye, 5 - 07 Ekim 2020 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu49456.2020.9302140
  • Basıldığı Şehir: Gaziantep
  • Basıldığı Ülke: Türkiye
  • Marmara Üniversitesi Adresli: Evet

Özet

© 2020 IEEE.In this study, a method for fast and efficient multiquery image retrieval from large scale databases is introduced. Images used as queries are semantically different from each other. In order to obtain similarity between multiple queries and each item in the database, image features are extracted from a deep networks and then they are converted into binary codes. The database items that simultaneously most closely resemble multiple queries are obtained by the Pareto front method. Furthermore, the method is tested on a designed graphical user interface.