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北海道大学 情報科学研究科 メディアダイナミクス研究室 Laboratory of Media Dynamics

研究業績

2021年度

2021年4月から2022年3月までの研究業績

著書

表示する研究業績がありません。

論文(学会誌)

  • Disentangled representation learning in real-world image datasets via image segmentation prior

    Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama

    IEEE Access

  • Detection of important scenes in baseball videos via bidirectional time lag aware deep multiset canonical correlation analysis

    Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

    IEEE Access

  • Domain adaptive cross-modal image retrieval via modality and domain translations

    Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama

    IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Science

  • Distress image retrieval for infrastructure maintenance via self-trained deep metric learning using experts’ knowledge

    Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

    IEEE Access

  • Text-guided style transfer-based image manipulation using multimodal generative models

    Ren Togo, Megumi Kotera, Takahiro Ogawa, Miki Haseyama

    IEEE Access

論文(国際会議)

  • Human-centered favorite music classification using EEG-based individual music preference deep time-series CCA

    Ryosuke Sawata, Takahiro Ogawa, Miki Haseyama

    2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

  • Semantic-aware unpaired image-to-image translation for urban scene images

    Zongyao Li, Ren Togo, Takahiro Ogawa, Miki Haseyama

    2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

  • Cross-domain semi-supervised deep metric learning for image sentiment analysis

    Yun Liang, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

    2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

  • Feature integration via semi-supervised ordinally multi-modal Gaussian process latent variable model

    Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

    2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

  • Estimation of visual features of viewed image from individual and shared brain information based on fMRI data using probabilistic generative model

    Takaaki Higashi, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

    2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

  • Multi-modal label dequantized gaussian process latent variable model for ordinal label estimation

    Masanao Matsumoto, Keisuke Maeda, Naoki Saito, Takahiro Ogawa, Miki Haseyama

    2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

  • Classification of expert-novice level using eye tracking and motion data via conditional multimodal variational autoencoder

    Yusuke Akamatsu, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama

    2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)

論文(技術報告)

表示する研究業績がありません。

講演発表(学会)

  • [招待講演]マルチメディアAI技術に基づく異分野融合研究と実社会応用

    映像情報メディア学会技術報告, vol.45, no.13, pp.73-80
    小川 貴弘, 長谷山 美紀

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