人工知能研究センター

関西学院大学
ホーム | メンバー | カレンダー・国際会議・学会 | オープンデータ |

About us

　本研究センターは，将来起こるであろう事象を精度高く予測する手法の構築を目的とし，それに関する研究を行なう組織です．Internet of Thingsによりもたらされる大量の実世界データに対し，Bayes LearningやDeep Learning，Reinforcement Learningなどの機械学習を適用した事象予測では精度に限界が生じると考えられます．本センターでは，既存の機械学習，確率過程としての時系列解析，人間の認知的・生理的側面を捉えた研究，とをそれぞれ発展させ，さらにそれらを融合することにより，将来に起こる事象を精度高く予測するための手法を明らかにすることを目標に研究活動を行ないます．
　本センターが主に研究する予測手法は，例えば，各種診断画像の時系列から病気の将来の進行度を予測したり，各企業が進む方向性や経済指標の予測など実社会への応用・適用を強く意識しております．さらに，人工知能の基礎的研究としても，現在の人工知能が苦手としている文脈に応じた解析に対して，人間の常識に関する研究の知見を取り込むことによってブレークスルーをもたらし得ると考えています．

人工知能関連の最近の成果

Journal Paper

  1. Asakawa, K., J. Hirano, T. Yamazaki, M. Kimura, Y. Yamazaki, K. Katahira, and N. Nagata (2024). Neural activity and sound impression induced by virtual bass for individuals who prefer bass-heavy audio. Applied Acoustics, 219, 109927.
  2. Zhuo, Y. and T. Morimoto (2024). A hybrid model for forecasting realized volatility based on heterogeneous autoregressive model and support vector regression, Risks, 12(1), 12. https://doi.org/10.3390/risks12010012.
  3. 杉本匡史, 長田典子, 西崎ちひろ, 田丸人意, 村井康二 (2024). 入出港場面におけるエキスパートとノービスのリスク認知プロセス―評価グリッド法を用いた可視化―. 日本航海学会論文集, 149, 56-66.
  4. 破田野智己, 竹澤智美, 杉本匡史, 東 泰宏, 渋田一夫, 長田典子 (2024). 観光動機に基づく外国人旅行者の分類および判別法の提案－観光事業におけるビスポークサービスの実現に向けて－，日本感性工学会論文誌, 23(1), 39-48.
  5. Shigemoto, H. and T. Morimoto (2023). On the usefulness of dynamically spilled risk: an optimal portfolio allocation based on cross-sector information contagion, Cogent Economics and Finance, 11(2), 2243200.
  6. 中井大貴, 河南壮太, 田原映理, 山本有貴, 福山 尚, 五味 文, 角所 考, 岡留 剛 (2023). 網膜剥離疾患のOCTスキャン画像における網膜層の抽出，電子情報通信学会論文誌D, Vol.J106-D (8), 419-430.
  7. Kitamura, Y., H. Toshima, A. Inokuchi, and D. Tanaka (2023). Bayesian optimization of the composition of the lanthanide metal-organic framework MIL-103 for white-light emission, Mol. Syst. Des. Eng., 8, 431-435.
  8. 濱田大佐, 杉本匡史, 山﨑陽一, 長田典子, 高原秀起, 竹厚 流, 加藤早紀 (2023). スマートフォン用保護フィルムの感性評価モデルの構築 -価値構造の個人差に基づく類型化-，日本感性工学会論文誌, 22(2), 207-216.
  9. Shigemoto, H. and T. Morimoto (2022). Forecasting High-Dimensional Covariance Matrices Using High-Dimensional Principal Component Analysis, Axioms, 11(12), 692.
  10. Shigemoto, H. and T. Morimoto (2022). Volatility spillover among Japanese sectors in response to COVID-19, Journal of Risk and Financial Management, 15(10), 480.
  11. 小林史弥, 杉本匡史, 青柳西蔵, 山本倫也, 長田典子 (2022). ビスポーク場面における販売員の発話内容のモデル化とコミュニケーションロボットを用いた実験による評価，ヒューマンインタフェース学会論文誌, 24(4), 263-272.
  12. 山﨑陽一, 飛谷謙介, 谿 雄祐, 井村誠孝, 亀井光仁, 長田典子 (2022). 感性工学的手法に基づく触感予測モデルの構築と評価〜布地触感予測の実現〜，電気学会論文誌C, 142(5), 616-624.
  13. 高木騰也, 藤井叙人, 片寄晴弘 (2022). 強さの異なる複数のAIエージェントによるオセロのための自然な棋力調整手法の提案，情報処理学会論文誌，63(11)，1602-1607.
  14. Furuya, S., R. Ishimaru, and N. Nagata (2021). Factors of choking under pressure in musicians. PLoS One. https://doi.org/10.1371/journal.pone.0244082.
  15. Miyoshi R., N. Nagata, and M. Hashimoto (2021). Enhanced convolutional LSTM with spatial and temporal skip connections and temporal gates for facial expression recognition from video. Neural Comput & Applic. https://doi.org/10.1007/s00521-020-05557-4.
  16. Shigemoto, H. and T. Morimoto (2021). An Integrated Framework for Visualizing and Forecasting Realized Covariance Matrices, Japanese Journal of Statistics and Data Science, 4, 697–730.
  17. 上井康平，角所 考，岡留 剛，大北陽一，福山 尚，木村亜紀子，五味 文 (2021)．両眼視差に基づく小児の間欠性外斜視の戻り予測．生体医工学誌, 59(2-3), p.72-75.
  18. 飛谷謙介，田口皓一，橋本 学，阪下啓祐，谷 伊織，橋本 翔，片平建史，長田典子 (2020). 多視点画像群を用いたDNNによる3次元物体の印象推定. 電子情報通信学会論文誌 D, J103-D(11), 844-848.
  19. Tobitani K., K. Nishijima, K. Katahira, and N. Nagata (2020). A visibility assessment of the design pattern of car tail lamps in terms of perceptual sensitivity on face recognition abilities. Cogent Engineering, 7(1), DOI: 10.1080/23311916.2020.1834934.
  20. Goto T., T. Sone, Y. Tani, K. Tobitani, and N. Nagata (2020). Modeling the relationship between the impressions and image features of crinkle finish of DSLR camera. J. Percept. Imaging, 3(2), 020503-1-020503-10.
  21. 高木一宏，岡留　剛 (2020)．潜在変数空間内の演算による顔画像の融合．電子情報通信学会誌D，J103-D, 10, 712-720.
  22. Komuku, Y., H. Ishikawa, A. Ide, T. Matsuoka, H. Fukuyama, T. Okadome, and F. Gomi (2020). Predictive biomarker for progression into the sunset glow fundus of Vogt-Koyanagi-Harada disease, using adaptive binarization of fundus photographs. Translational Vision Science and Technology (TVST), 9(11), Art.1, 10-10.
  23. Nakaguchi, E., K. Noda, K. Osaki, and K. Uemichi (2020). Global attractor for a two-dimensional chemotaxis system with linear degradation and indirect signal production. Jpn J. Ind. Appl. Math., 37(1), 49-80.
  24. Komuku, Y., A. Ide, H. Fukuyama, H. Masumoto, H. Tabuchi, T. Okadome, and F. Gomi (2020). Choroidal thickness estimation from colour fundus photographs by adaptive binarisation and deep learning, according to central serous chorioretinopathy status. Scientific Report, 10, 1．
  25. Shigemoto, H. and T. Morimoto (2020). Dependency structure analysis of the Japanese stock market based on realized networks (in Japanese: 実現ネットワークによる日本株の依存構造分析). 日本統計学会誌, 49, 241-264.
  26. 猪股健太郎，藤井 豪，橋本 翔，片平建史，長田典子，浅野 隆，河崎圭吾，荷方邦夫 (2020). 自動車外観デザインに対する印象と選好の関係性に基づく個人の類型化．日本感性工学会論文誌, 19(2), 223-233.
  27. 青柳西蔵，山﨑陽一，小野友己，山本倫也，長田典子 (2020). ラバン行動分析と感度分析に基づくモノづくりの場における身体感情表現タイプの抽出．ヒューマンインタフェース学会論文誌, 22(1), 1-12.
  28. 楠見昌司，飛谷謙介，山﨑陽一，谿 雄祐，長田典子 (2020). グローブボックス開き挙動における好まれる印象再現の検討．自動車技術会論文集, 51(2), 374-378.
  29. 上井康平，角所 考，岡留 剛，福山 尚，五味 文 (2020)．Enface OCTによる眼底画像中のDONFLの病変経過予測．電子情報通信学会論文誌 D, J103-D(4), pp.359-362．
  30. 田中哉汰, 藤井叙人, 片寄晴弘 (2020)．GANによる教師なし3次元姿勢推定の精度向上に向けての一検討．エンタテインメントコンピューティング（EC）研究報告, 2020-EC-55(23), 1-3．
  31. Aoki, T. and K. Osaki (2019). Bifurcations with multi-dimensional kernel in a chemotaxis-growth system.Scientiae Mathematicae Japonicae (SCMJ) 82(2), 155-169.
  32. Noda, K. and K. Osaki (2019). Global attractor and lyapunov function for one-dimensional deneubourg chemotaxis system. Hiroshima Math. J., 49(2), 251-271.
  33. Hashida, M. and H. Katayose (2019). A study of phrase structure perception using the PEDB second edition. International Symposium on Performance Science (ISPS).
  34. Nugroho, D. B. and T. Morimoto (2019). Incorporating realized quarticity into a realized stochastic volatility model. Asia-Pacific Financial Markets, 26, 495-528. https://doi.org/10.1007/s10690-019-09276-2.
  35. Hanafusa, R. and T. Okadome (2019). Bayesian kernel regression for noisy inputs based on Naradaya-Watson estimator constructed from noiseless training data. Advances in Data Science and Adaptive Analysis, 12(1), 2050004.
  36. Yagiri, H. and T. Okadome (2019). Simple and complete resynchronization for wireless sensor networks. IEICE Transactions on Communication, E102-B, 4, 679-689.
  37. Hashimoto, S., A. Yamada, and N. Nagata (2019). A quantification method of composite impression of products by externalized evaluation words of the appraisal dictionary with review text data, International Journal of Affective Engineering, 18(2), 59-65.
  38. 安東俊之介, 藤井叙人, 片寄晴弘 (2019)．UPP (Unreal Prank Painter)：悪戯の楽しみに着目した落書きコンテンツ．情報処理学会論文誌, 60(11), 1983-1991．
  39. 渡邊桃吾, 片寄晴弘 (2019)．Ball in Bowl：日常ストレスからの解放を目的としたタブレットアプリケーション．情報処理学会論文誌, 60(11), 2030-2033．
  40. 鎌田稜平，角所 考，飯山将晃，西口敏司，村上正行 (2019)．受講者の挙動の観測に基づく友人関係の推定．教育システム情報学会誌，36(2)．
  41. 鈴木秀通，飛谷謙介，橋本 翔，山田篤拓，長田典子 (2019). レビューテキストと画像を用いた機械学習によるプロダクトの感性指標構築．精密工学会誌, 85(12), 1143-1150.
  42. 鳴海孝之，陰山真矢，上道賢太，本多久夫，大崎浩一 (2019)．ミツバチの営巣初期過程に対するエージェントベースモデル．昆虫と自然，54(9), 35-37．【招待寄稿】
  43. 杉本匡史，山本倫也，長田典子 (2019)．自発的に楽しむモノづくりにおいて喚起される感情－その性質と喚起タイミング－，ヒューマンインタフェース学会論文誌，21(1)，85-96．
  44. Narumi, T., K. Uemichi, H. Honda, and K. Osaki (2018). Self-organization at the first stage of honeycomb construction: Analysis of an attachment-excavation model, PLoS ONE, 13(10), e0205353.
  45. Okamoto, K., K. Kakusho, M. Yamamoto, T. Kojima, and M. Murakami (2018). Estimating work situations from videos of practical training classes with assembly tasks. International Journal of Information and Education Technology, 8(1), 38-45.
  46. Nakaguchi, E. and K. Osaki (2018). Global existence of solutions to an n-dimensional parabolic-parabolic system for chemotaxis with logistic-type growth and superlinear production. Osaka Math J., 55, 51-70.
  47. Katahira, K., Y. Yamazaki, C. Yamaoka, H. Ozaki, S. Nakagawa, and N. Nagata (2018). EEG correlates of the flow state: A combination of increased frontal theta and moderate frontocentral alpha rhythm in the mental arithmetic task. Frontiers in Psychology, 9, 300.
  48. 西川純貴，角所 考，飯山将晃，西口敏司，村上正行 (2018). RGB-Dカメラを用いた顔観測による講義室内の受講者の着席位置推定，教育システム情報学会誌，35(2)，151-156.
  49. 山田篤拓，橋本 翔，長田典子 (2018)．レビューデータを用いた評価表現辞書に基づく印象の自動指標化，日本感性工学会論文誌，17(5)，567-576．
  50. 谿 雄祐，藤原大志，竹本 敦，飛谷謙介，井村誠孝，長田典子 (2018)．テクスチャの印象における視触覚情報統合様式に関する検討，日本バーチャルリアリティ学会論文誌，23(3)，115-118．
  51. 佐々木康輔, 渡邉健斗, 橋本 学, 長田典子 (2018). 顔キーポイントの移動方向コードに基づく個人差の影響を受けにくい表情認識. 電気学会論文誌C, 138(5), 611-618.
  52. 橋本 翔, 田中一晶, 片平建史, 長田典子 (2018). 刺激と独立な個人の傾向を考慮した新たな三相データの分析法. 行動計量学, 45(1), 27-38.
  53. Morimoto, T. and Y. Kawasaki (2017). Volatility forecasting with empirical similarity: Japanese stock market case. JSM Proceedings, Statistical Computing Section. Baltimore, MD: American Statistical Association, 2483-2510.
  54. Aoki, T. and K. Osaki (2017). Bifuractions with multi-dimensionak kernel in a chemotaxis-growth system. Scientiae Mathematicae Japonicae (SCMJ), online ver. e-2017-19.
  55. 菅野 隼，松重龍之介，岡留 剛 (2017). センサデータによる行動認識のためのベイズ的隠れマルコフモデルの拡張と適用. 情報処理学会論文誌, 58(10), 1688-1700．
  56. 金川絵利子，岡留 剛 (2017). カーネル法による構文に着目した作家の文体の特徴づけと類似性分析. 人工知能学会論文誌, 32(3), F-G94_1-14．
  57. 福島良平，片寄晴弘 (2017). 2Dアクションゲームにおける島モデルGAを用いた多様な振舞いの獲得. 情報処理学会論文誌, 58(11), 1-9.
  58. Morimoto, T. and Y. Kawasaki (2017). Forecasting financial market volantility using a dynamic topic model, Asia-Pacific Financial Markets, 24, 149-167.
  59. 清水琢也，岡留 剛 (2016). Dynamic Stacked Topic Model -階層構造を持つ文書に対する動的トピックモデル-. 人工知能学会論文誌, 31(2), 1-8.
  60. Ohmura, M., K. Kakusho, and T. Okadome (2014). Tweet sentiment analysis with Latent Dirichlet Allocation. International Journal of Information Retrieval Research, 4(3), 66-79.
  61. 中島潤耶，岡留 剛 (2013). 実写ムービーコンテンツ作成支援システムの設計と実装. 情報処理学会論文誌, 54(12), 2427-2439.
  62. 喜住祐紀，角所 考，舩冨卓哉，飯山将晃，岡留 剛 (2013). レベルセット法を用いたF陣形と個人空間の抽出によるオープンスペース内の偶発的対面インタラクションの参与者グループ認識. 電子情報通信学会論文誌 A, J96-A(10), 705-720.
  63. Okadome, T., H. Funai, S. Ito, J. Nakajima, and K. Kakusho (2012). Retrieval of web pages on real-world events related to physical objects. International Journal of Information Retrieval Research (IJIRR), 2(1), 65-80.
  64. Okadome, T., H. Funai, S. Ito, J. Nakajima, and K. Kakusho (2012). Web search for real-world events and actions. International Journal of Computer and Communication Engineering (IJCCE), 1(3), 84-88.

International Conference

  1. Taniuchi, Y. and K. Takahashi (2024). Spatial representation and reasoning about fold strata: A qualitative approach, 15th International Conference (ICAART 2023), 244-266.
  2. Kihara, M., D. Hamada, and N. Nagata (2024). Possible acquired synesthesia underlying the consistency of favorable colors -A case study of grapheme-color synesthesia and sound-color synesthesia among competitive karuta players-, The 10th International Society of Affective Science and Engineering (ISASE2024), AM-1C, C000046.
  3. Yajima, Y., J. Kato, and A. Inokuchi (2023). The third common interface for graph neural networks, Proc. of International Joint Conference on Neural Networks, 1-8.
  4. T. Morimoto (2023). Forecasting high-dimensional covariance matrices using high-dimensional principal component analysis, International Symposium on Recent Advances in Theories and Methodologies for Large Complex Data, https://www.math.tsukuba.ac.jp/~aoshima-lab/Flyer2023.pdf
  5. Takahashi, K. and H. Miwa (2023). Topological conditions and solutions for repairing argumentation frameworks, 5th International Conference on Logic and Argumentation (CLAR2023), 101-118, LNAI 14156, Springer-Verlag.
  6. Yagi, A., T. Akiyama, M. Kageyama, and K. Osaki (2023). Asymptotic behavior of solutions for honeycomb construction model, The Fifth Workshop on Interdisciplinary Sciences (WIS2023): A Satellite Meeting of the 10th International Congress on Industrial and Applied Mathematics (ICIAM 2023 Tokyo).
  7. Kageyama, M., T. Akiyama, and K. Osaki (2023). A PDE model for the first stage of honeycomb construction (poster), OKO (Oxford, Kyoto, and Ohio universities) International Symposium 2023: Mathematical Biology from Genes to Cells to Humans.
  8. Toga, M., M. Sugimoto, Y. Yamazaki, T. Hatano, N. Nagata, H. Fukuda, and K. Takata (2023). Comparison of sense of sustainability and premium components in Japan -A study using the evaluation grid method-, International Conference of Serviceology 2023 (ICServ2023), O3-03.
  9. Sugimoto, M., Y. Yagi, and N. Nagata (2023). How different tourist sites evoke different emotions: Investigation focusing on the urban and rural sites in Japan, Human-Computer Interaction (HCII 2023), Lecture Notes in Computer Science, 14012, 332–343.
  10. Taniuchi, Y. and K.Takahashi (2023). Qualitative Spatial Representation and Reasoning about Fold Strata, Proceedings of the 15th International Conference on Agents and Artificial Intelligence (ICAART2023), 211-220.
  11. Sugiyama, Y., N. Sunda, K. Tobitani, and N. Nagata (2023). Texture synthesis based on aesthetic texture perception using CNN style and content features, International Workshop on Frontiers of Computer Vision (IW-FCV2023), P1-3, 368-384.
  12. Tsumura, E., K. Tobitani, M. Toga, and N. Nagata (2023). Impression estimation of suit patterns based on style features using multi-scale CNN, International Workshop on Frontiers of Computer Vision (IW-FCV2023), P2-4, 554-568.
  13. Gregorius, B. and T. Okadome (2022). Generating code-switched text from monolingual text with dependency tree. Proceedings of the 20th Annual Workshop of the Australasian Language Technology Association.
  14. Naito, K. and K. Kakusho (2022). Segmentation of Indoor Daily Living Environments into Regions Used for Different Purposes, IEEE International Conference on Systems, Man, and Cybernetics, 967-973.
  15. Hayashi, T., K. Kakusho, T. Kitahashi, T. Matsumoto, and N. Sugano (2022). Classifying Situations for Collaboration among Medical Staff from Operating Room Videos, IEEE International Conference on System, Man, and Cybernetics, 2387-2393.
  16. Yajima, Y. and A. Inokuchi (2022). Why Deeper Graph Neural Network Performs Worse? Discussion and Improvement About Deep GNNs. Proc. of International Conference on Artificial Neural Networks, Part 2, 731-743.
  17. Takahashi. K (2022). Odd or Even: Handling N-lemmas in a Dynamic Argumentation Framework, The Fourth International Workshop on Systems and Algorithms for Formal Argumentation (SAFA2022), 5-18.
  18. Miyoshi, R., S. Akizuki, K. Tobitani, N. Nagata, and M. Hashimoto (2022). Convolutional Neural Tree for Video-Based Facial Expression Recognition Embedding Emotion Wheel as Inductive Bias, 2022 IEEE International Conference on Image Processing (ICIP2022), 3261-3265.
  19. Kuwamura, H., T. Ide, and H. Miwa (2022). Self-positioning Method Based on Similarity Between Environmental Map and Information of Image and Point Cloud, 14th International Conference on Intelligent Networking and Collaborative System.
  20. Hayashida, N. and H. Miwa (2022). Obstacle Detection Support System Using Monocular Camera, 14th International Conference on Intelligent Networking and Collaborative System.
  21. Enomoto, M., K. Takeoka, D. Yuyang, M. Oyamada, and T. Okadome (2021). Quality control for hierarchical classification with incomplete annotations. 25th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021).
  22. Yamada R., S. Hashimoto, and N. Nagata (2020). Extracting Kansei evaluation index using time series text data: Examining universality and Temporality. HCI International 2020 - Posters (HCII2020), CCIS 1226, 722-729.
  23. Sunda N., K. Tobitani, I. Tani, Y. Tani, N. Nagata, and N. Morita (2020). Impression estimation model for clothing patterns using neural style features. HCI International 2020 - Posters (HCII2020), CCIS 1226, 689-697.
  24. Sugimoto M., F. Zhang, N. Nagata, K. Kurihara, S. Yuge, M. Takata, K. Ota, and S. Furukawa (2020). Components of comfort in the office and its individual differences. ISMICT2020, Regular Session I.
  25. Hanafusa, R., J. Ebara, and T. Okadome (2020). Infinite mixtures of Gaussian process experts with latent variables and its application to terminal location estimation from multiple-sensor values, Proceedings of Intelligent System Conference (IntelliSys2010).
  26. Tosue, M. and K. Takahashi (2019). Towards a qualitative reasoning on shape change and object division. 14th International Conference on Spatial Information Theory (COSIT 2019), 7:1-7:15, LIPICS Vol. 142, ISBN 978-3-95977-115-3.
  27. Kawasaki, T., S. Moriguchi, and K. Takahashi (2019). Hybrid reasoning on a bipolar argumentation framework. The 13th international conference on Scalable Uncertainty Management (SUM 2019), 79-92, LNCS 11940, ISBN 978-3-030-35514-2. Springer-Verlag.
  28. Narumi, T., K. Uemichi, H. Honda, and K. Osaki (2019). An agent-based model for understanding symmetric alignment of honeycomb. Symmetry: Art and Science -11th Congress and Exhibition.
  29. Kotakehara, Y., K. Kakusho, S. Nishiguchi, M. Iiyama, and M. Murakami (2019). The classification of different situations in a lecture based on students' observed postures. HCI INTERNATIONAL 2019.
  30. Sakata, K., K. Kakusho, M. Iiyama, and S. Nishiguchi (2019). Observation planning for identifying each person by a drone in indoor daily living environment. HCI INTERNATIONAL 2019.
  31. Morimoto, T (2019). Economic policy uncertainty and financial market volatility: Evidence from Japan. The 62nd International Statistical Institute World Statistics Congress 2019 (ISI-WSC 2019).
  32. Miyoshi, R., N. Nagata, and M. Hashimoto (2019). Facial-expressionrecognition from video using enhanced convolutional LSTM. 2019 Digital Image Computing: Techniques and Applications (DICTA), 1-6.
  33. Hashimoto, S., T. Shimozono, and N. Nagata (2019). Bayesian estimation of impression discriminant ability in paired comparison. Data Science, Statistics & Visualization 2019 (DSSV2019), 46.
  34. Yamazaki, Y., M. Imura, K. Tobitani, Y. Tani, and N. Nagata (2019). Development of measurement and simulation scheme for digitalization of tactile perception. Proc. the Seventh Asia International Symposium on Mechatronics (AISM2019), 981-986.
  35. Suzuki, H., A. Yamada, K. Tobitani, S. Hashimoto, and N. Nagata (2019). An automatic modeling method of Kansei evaluation from product data using a CNN model expressing the relationship between impressions and physical features. Stephanidis, C. (ed.), HCI International 2019 (HCII 2019), CCIS, 1032, 86-94.
  36. Yamazaki, Y., M. Imura, and N. Nagata (2019). Tactile presentation scheme based on physiological characteristics of the fingertip. Stephanidis C. (ed.), HCI International 2019 (HCII 2019), CCIS, 1032, 172-179.
  37. Miyai, S., K. Katahira, M. Sugimoto, N. Nagata, K. Nikata, and K. Kawasaki (2019). Hierarchical structuring of the impressions of 3D shapes targeting for art and non-art university students. Stephanidis C. (ed.), HCI International 2019 (HCII 2019), CCIS, 1032, 385-393.
  38. Tosue, M., S. Moriguchi, and K. Takahashi (2019). Operations for shape transformations based on angles, Proceedings of the 11th International Conference on Agents and Artificial Intelligence (ICAART2019), 576-583.
  39. Fujiwara, T., Y. Tani, A. Takemoto, K. Tobitani, and N. Nagata (2019). Interaction of visual and haptic impressions in visuo-haptic texture cognition, 2019 IEEE International Conference on Consumer Electronics (ICCE), 673-674.
  40. Takemoto, A., K. Tobitani, Y. Tani, T. Fujiwara, Y. Yamazaki, and N. Nagata (2019). Texture synthesis with desired visual impressions using deep correlation feature, 2019 IEEE International Conference on Consumer Electronics (ICCE), 739-740.
  41. Takeoka, K., M. Oyamada, S. Nakadai, and T. Okadome (2019). Meimei: an efficient probabilistic approach for semantically annotating tables. Proceedings of the 33rd AAAI Conference on Artificial Intelligence. Accepted for presentation.
  42. Kawasaki, T., S. Moriguchi, and K. Takahashi (2018). Transformation from PROLEG to a bipolar argumentation framework, The Second International Workshop on Systems and Algorithms for Formal Argumentation (SAFA2018), 36-47.
  43. Monno, S., Y. Kamada, H. Miwa, and K. Ashida (2018). Detection of defects on SiC substrate by SEM and classification using deep learning, Proc. International Conference on Intelligent Networking and Collaborative System, 47-58.
  44. Senda, A., M. Takagi, H. Miwa, and E. Watanabe (2018). Three-dimensional motion tracking system for extracting spatial movement pattern of small fishes, Proc. International Conference on Intelligent Networking and Collaborative System, 158-169.
  45. Sunda, N., K. Tobitani, A. Takemoto, I. Tani, Y. Tani, T. Fujiwara, N. Nagata, and N. Morita (2018). Impression estimation model and pattern search system based on style features and Kansei metric, 24th ACM Symposium on Virtual Reality Software and Technology (VRST'18), P3-09.
  46. Tobitani, K., T. Matsumoto, Y. Tani, and N. Nagata (2018). Modeling the relation between skin attractiveness and physical characteristics, Proc. the 2018 International Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia (MMArt&ACM'18), 30-35.
  47. Obata, K., M. Sugimoto, and N. Nagata (2018). Optimization of motorcycle riders categorization based on emotion using decision tree analysis, The 11th IEEE Pacific Visualization Symposium (PacificVis 2018), 136.
  48. Takemoto, A., T. Fujiwara, K. Tobitani, Y. Tani, and N. Nagata (2018). Camparison of visual impression given by texture of real surfaces and synthesized images, The 11th IEEE Pacific Visualization Symposium (PacificVis 2018), 124.
  49. Fujiwara, T., A. Takemoto, Y. Tani, K. Tobitani, and N. Nagata (2018). The integration of visual and haptic impressions felt form synthetic resin texture, The 11th IEEE Pacific Visualization Symposium (PacificVis 2018), 113.
  50. Hanafusa, R. and T. Okadome (2018). Regression method for noisy inputs based on non-parametric estimator constructed from noiseless training data, Proceedings of the 3rd International Conference on Computational Intelligence and Applications (ICMU2018).
  51. Yagiri, H. and T. Okadome (2018). Recovery of synchronization for wireless sensor networks, Proceedings of the 11th International Conference on Mobile Computing and Ubiquitous Network (ICCIA2018).
  52. Noda, K. and K. Osaki (2018). Global attractor and lyapunov function for one-dimensionak deneubourg chemotaxis system. 3rd International Workshop on Mathematical Analysis of Chemotaxis (iWMAC3).
  53. Osaki, K., K. Noda, K. Uemichi, and E. Nakaguchi (2018). Global-in-time existence and asymptotic behavior of solutions to a chemotaxis model for the nest building of termites. 3rd International Workshop on Mathematical Analysis of Chemotaxis (iWMAC3).
  54. Taguchi, K., M. Hashimoto, K. Tobitani, and N. Nagata (2018). An estimation method of human impression factors for objects from their 3D shapes using a deep neural network, Proceedings of the IS&T International Symposium on Electronic Imaging 2018 (Image Processing: Algorithms and Systems XVI), IPAS-194.
  55. Yamada, A., S. Hashimoto, and N. Nagata (2018). A text mining approach for automatic modeling of kansei evaluation from review texts. Proceedings of the 7th International Conference on Kansei Engineering and Emotion Reserach 2018 (KEER2018), Springer, 739, 319-328.
  56. Tsukamoto, M., K. Kakusho, M. Iiyama, and S. Nishiguchi (2017). Estimating the target of interaction for each human in office space with obstacles using 3D observation. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (SMC2017).
  57. Omi, T. K. Kakusho, M. Iiyama, and S. Nishiguchi (2017). Segmentation and tracking of object when grasped and moved within living spaces. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (SMC2017), 3147-5152.
  58. Kanagawa, E. and T. Okadome (2016). Syntactic characteristics and similarities of Japanese authors’ writing styles: A kernel-based approach, Proceedings of the 20th International Conference on Asian Language Processing (IALP2016), 59-62.
  59. Kitagawa, M. and T. Okadome (2015). Recovering missing data in three dimensional gait measurement, Proceedings of IEEE TENCON 2015, 1-6.
  60. Matsushige, R., K. Kakusho, and T. Okadome (2015). Semi-supervised learning based activity recognition from sensor data. Proceedings of IEEE 4th Global Conference of Consumer Electronics, (GCCE2015), 106-107.
  61. Kikutani, S., K. Kakusho, T. Okadome, M. Iiyama, and S. Nishiguchi (2015). Measuring the arrangement of multiple information devices by observing their user’s face. Proceedings of 3rd International Conference of Distributed, Ambient, and Pervasive Interactions (DAPI2015), LNCS 9189, 296-304.
  62. Ohmura, M., K. Kakusho, and T. Okadome (2014). Social mood extraction from Twitter posts with document topic model. Proceedings of the 5th International Conference on Information Science and Applications (ICISA2014), 357-360.
  63. Kizumi, Y., K. Kakusho, T. Okadome, T. Funatomi, and M. Iiyama (2012). Detection of social interaction from observation of daily living environments. Proceedings of the 1st International Conference on Future Generation Communication Technologies (FGCT2012), 162-167.
  64. Okadome, T., J. Nakajima, S. Ito, and K. Kakusho (2011). An accessible coded input method for Japanese extensive writing. Proceedings of the Workshop on Advances in Text Input Methods (WTIM 2011), 31-37.