Image description generation without image processing using fuzzy inference

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

We propose a sentence generation method that describes images. We do not use image processing technique in our proposed method. Human annotated image tags are used as image information to generate sentence. By using human annotated tags, we think this enables to describe image more relevant and user specific. Our method uses Kyoto University's case frame data and Google N-gram to generate candidate sentences. We extend these candidates to describe images more relevant. To be more precise, we added segments with missing semantic role, and added modification segments. To select one output sentence, we used fuzzy rules to grade naturalness of candidate sentences. To grading image relevance of the sentence, we scored word similarity for each word. The performance of the proposed system has been evaluated by subjective experiments and obtained satisfactory results.

元の言語English
ホスト出版物のタイトル2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
DOI
出版物ステータスPublished - 2012 10 23
イベント2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 - Brisbane, QLD, Australia
継続期間: 2012 6 102012 6 15

出版物シリーズ

名前IEEE International Conference on Fuzzy Systems
ISSN(印刷物)1098-7584

Other

Other2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
Australia
Brisbane, QLD
期間12/6/1012/6/15

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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  • これを引用

    Ito, N., & Hagiwara, M. (2012). Image description generation without image processing using fuzzy inference. : 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 [6250835] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZ-IEEE.2012.6250835