過去のお知らせ
IEEE GCCE2022に11件の発表を行い、2件が受賞しました！
10月18日～21日に大阪 千里ライフサイエンスセンターにて開催された国際会議2022 IEEE 11th Global Conference on Consumer Electronics (IEEE GCCE 2022)に当研究室より以下の11件の発表を行いました。
また、2件の発表が受賞しました！おめでとうございます！
・ Excellent Poster Award, Silver Prize ([10]の発表）
・ Excellent Student Poster Award, Silver Prize（[7]の発表）
[1] He Zhu, Ren Togo, Takahiro Ogawa, Miki Haseyama: “A Multimodal Interpretable Visual Question Answering Model Introducing Image Caption Processor”
[2] Tsubasa Kunieda, Ren Togo, Noriko Nishioka, Yukie Shimizu, Shiro Watanabe, Kenji Hirata, Keisuke Maeda, Takahiro Ogawa, Kohsuke Kudo, Miki Haseyama: “Prediction of Amyloid-β Positivity Using QSM Images Based on Bootstrap Your Own Latent”
[3] Ryo Shichida, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Analysis of Relationships Between Visual Cognitive Contents and Response of Each Brain Region via Visual Question Answering”
[4] Hiroki Okamura, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama: “GCN-Based Collaborative Filtering Considering Personality Bias”
[5] Huaying Zhang, Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Cross-Modal Image Retrieval Considering Semantic Relationships With Object Information”
[6] Yuhu Feng, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Refinement of Gaze-Based Image Caption for Image Retrieval”
[7] Yuki Era, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Content-Based Image Retrieval Using Effective Synthesized Images From Different Camera Views via pixelNeRF”
[8] Ryota Goka, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Shoot Event Prediction From Soccer Videos by Considering Players’ Spatio-Temporal Relations”
[9] Kazuki Yamamoto, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Cross-Platform Recommendation Considering Common Users’Preferences Based on Preference Propagation GraphNet”
[10] Masato Kawai, Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Free-Viewpoint Sports Video Generation Based on Dynamic NeRF Considering Time Series”
[11] Yutaka Yamada, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Trend Prediction of Students’Mock Examination Results Using Matrix Completion”
