1 Ocak 2017 Dergi makalesi Açık Erişim

Kilickaya, Mert; Akkus, Burak Kerim; Cakici, Ruket; Erdem, Aykut; Erdem, Erkut; Ikizler-Cinbis, Nazli

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  "@context": "https://schema.org/", 
  "@id": 46249, 
  "@type": "ScholarlyArticle", 
  "creator": [
    {
      "@type": "Person", 
      "affiliation": "Hacettepe Univ, Dept Comp Engn, Ankara, Turkey", 
      "name": "Kilickaya, Mert"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Middle East Tech Univ, Dept Comp Engn, Ankara, Turkey", 
      "name": "Akkus, Burak Kerim"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Middle East Tech Univ, Dept Comp Engn, Ankara, Turkey", 
      "name": "Cakici, Ruket"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Hacettepe Univ, Dept Comp Engn, Ankara, Turkey", 
      "name": "Erdem, Aykut"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Hacettepe Univ, Dept Comp Engn, Ankara, Turkey", 
      "name": "Erdem, Erkut"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Hacettepe Univ, Dept Comp Engn, Ankara, Turkey", 
      "name": "Ikizler-Cinbis, Nazli"
    }
  ], 
  "datePublished": "2017-01-01", 
  "description": "In the past few years, automatically generating descriptions for images has attracted a lot of attention in computer vision and natural language processing research. Among the existing approaches, data-driven methods have been proven to be highly effective. These methods compare the given image against a large set of training images to determine a set of relevant images, then generate a description using the associated captions. In this study, the authors propose to integrate an object-based semantic image representation into a deep features-based retrieval framework to select the relevant images. Moreover, they present a novel phrase selection paradigm and a sentence generation model which depends on a joint analysis of salient regions in the input and retrieved images within a clustering framework. The authors demonstrate the effectiveness of their proposed approach on Flickr8K and Flickr30K benchmark datasets and show that their model gives highly competitive results compared with the state-of-the-art models.", 
  "headline": "Data-driven image captioning via salient region discovery", 
  "identifier": 46249, 
  "image": "https://aperta.ulakbim.gov.tr/static/img/logo/aperta_logo_with_icon.svg", 
  "license": "http://www.opendefinition.org/licenses/cc-by", 
  "name": "Data-driven image captioning via salient region discovery", 
  "url": "https://aperta.ulakbim.gov.tr/record/46249"
}