Classification of photo and sketch images using convolutional neural networks

Kazuma Sasaki, Madoka Yamakawa, Kana Sekiguchi, Tetsuya Ogata

    研究成果: Conference contribution

    2 引用 (Scopus)

    抜粋

    Content-Based Image Retrieval (CBIR) system enables us to access images using only images as queries, instead of keywords. Photorealistic images, and hand-drawn sketch image can be used as a queries as well. Recently, convolutional neural networks (CNNs) are used to discriminate images including sketches. However, the tasks are limited to classifying only one type of images, either photo or sketch images, due to the lack of a large dataset of sketch images and the large difference of their visual characteristics. In this paper, we introduce a simple way to prepare training datasets, which can enable the CNN model to classify both types of images by color transforming photo and illustration images. Through the training experiment, we show that the proposed method contributes to the improvement of classification accuracy.

    元の言語English
    ホスト出版物のタイトルArtificial Neural Networks and Machine Learning - 25th International Conference on Artificial Neural Networks, ICANN 2016, Proceedings
    出版者Springer Verlag
    ページ283-290
    ページ数8
    9887 LNCS
    ISBN(印刷物)9783319447803
    DOI
    出版物ステータスPublished - 2016
    イベント25th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2016 - Barcelona, Spain
    継続期間: 2016 9 62016 9 9

    出版物シリーズ

    名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    9887 LNCS
    ISSN(印刷物)03029743
    ISSN(電子版)16113349

    Other

    Other25th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2016
    Spain
    Barcelona
    期間16/9/616/9/9

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

    フィンガープリント Classification of photo and sketch images using convolutional neural networks' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Sasaki, K., Yamakawa, M., Sekiguchi, K., & Ogata, T. (2016). Classification of photo and sketch images using convolutional neural networks. : Artificial Neural Networks and Machine Learning - 25th International Conference on Artificial Neural Networks, ICANN 2016, Proceedings (巻 9887 LNCS, pp. 283-290). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 9887 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-44781-0_34