Y MOROTO Yuya Moroto

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  • Yuya Moroto

Yuya Moroto
My researches lie in affective computing, especially, how to make computers understand the semantics perceived by humans. I am interested in the relationships between multimedia contents and biological signals, and then apply techniques from various fields such as multi-modal machine learning, probabilistic generative model, tensor analysis etc.
IEEE Graduate Student Member，IEICE Student Member．B.S. (Engineering)，M.S. (Information Science)．

[CV] in English updated on July 12, 2021

E-mail: moroto [at] lmd [dot] ist [dot] hokudai [dot] ac [dot] jp


BioGraphy Research Achievement Research Activities Awards Others Visitor

 

Biography

Education

  • Apr. 2012 – Mar. 2015 Yokkaichi High School
  • Apr. 2015 – Mar. 2019 B.S., School of Engineering, Hokkaido Univ., Japan
  • Apr. 2019 – Mar. 2021 M.S., Graduate School of Information Science and Technology, Hokkaido Univ., Japan
  • Apr. 2021 – Present Ph.D., Graduate School of Information Science and Technology, Hokkaido Univ., Japan

Research

  • Aug. 2016 – Sep. 2016 Mitsubishi Chemical Holdings Group Intern
  • Apr. 2021 – Present JSPS Research Fellow DC1
  • Apr. 2021 – Present Part-time Lecturer at Hokkai-Gakuen Univ.
  • Jul. 2021- Present MEXT Doctoral program for Data-Related InnoVation Expert (D-DRIVE), Super Research Assistant [link]
  • Sep. 2021- Oct. 2021 CyberAgent AI Lab Reserch Intern

 

Research Achievement

Journal

  1. Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Human-Centric Emotion Estimation Based on Correlation Maximization Considering Changes with Time in Visual Attention and Brain Activity,” IEEE Access, vol. 8, pp. 203358-203368, 2020. (2020IF 3.745)  [paper]
  2. Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Few-shot Personalized Saliency Prediction Based on Adaptive Image Selection Considering Object and Visual Attention,” Sensors 20, no. 8: 2170, 2020. (2020IF 4.066)  [paper]
  3. Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Tensor-Based Emotional Category Classification via Visual Attention-Based Heterogeneous CNN Feature Fusion,” Sensors 20, no. 7: 2146, 2020. (2020IF 4.066)  [paper]

International Conference

  1. 〇Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Visual Sentiment Prediction Using Cross-way Few-Shot Learning Based on Knowledge Distillation,” in Proceedings of IEEE International Conference on Image Processing (ICIP) (accepted for publication)
  2. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Few-shot Personalized Saliency Prediction with Similarity of gaze Tendency Using Object-based Structual Information,” in Proceedings of IEEE International Conference on Image Processing (ICIP) (accepted for publication)
  3. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Human Emotion Recognition Using Multi-Modal Biological Signals Based on Time Lag-Considered Correlation Maximization,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4683-4687, 2022.5. [link] [presentation file]
  4. 〇Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “EVisual Sentiment Prediction Using Few-shot Learning via Distribution Relations of Visual Features,” in Proceedings of IEEE Global Conference on Consumer Electronics (GCCE), pp.217-218, 2021.10.
  5. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Few-Shot Personalized Saliency Prediction Using Person Similarity Based on Collaborative Multi-Output Gaussian Process Regression,” in Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 1469-1473, 2021.9.  [link]  [presentation file]
  6. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Human Emotion Estimation Using Multi-Modal Variational AutoEncoder with Time Changes,” in Proceedings of IEEE Global Conference on Life Sciences and Technologies (LifeTech), pp.82-83, 2021.3. [link]
  7. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Estimation of User-Specific Visual Attention Considering Individual Tendency Toward Gazed Objects,” in Proceedings of IEEE Global Conference on Consumer Electronics (GCCE), pp.554-555, 2020.10. [link]
  8. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Estimation of Person-Specific Visual Attention via Selection of Similar Persons,” in Proceedings of IEEE International Conference on Consumer Electronics – Taiwan (ICCE-TW), pp.1-2, 2020.9. [link]
  9. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Estimation of User-Specific Visual Attention Based on Gaze Information of Similar Users,” in Proceedings of IEEE Global Conference on Consumer Electronics (GCCE), pp.486-487, 2019.10. [link]
  10. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Estimation of Emotion Labels via Tensor-based Spatiotemporal Visual Attention Analysis,” in Proceedings of IEEE International Conference on Image Processing (ICIP), pp.4105-4109, 2019.9. [link]
  11. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “User-Specific Visual Attention Estimation Based on Visual Similarity and Spatial Information in Images,” in Proceedings of IEEE International Conference on Consumer Electronics – Taiwan (ICCE-TW), pp.479-480, 2019.5. [link]
  12. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Estimation of Visual Attention via Canonical Correlation between Visual and Gaze-based Features,” in Proceedings of IEEE Global Conference on Life Sciences and Technologies (LifeTech), pp.229-230, 2019.3. [link]
  13. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “User-centric Visual Attention Estimation Based on Relationship Between Image and Eye Gaze Data,” in Proceedings of IEEE Global Conference on Consumer Electronics (GCCE), pp.44-45, 2018.10. [link]

Domestic Conference (Japanese)

  1. 〇Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Few-shot personalized saliency prediction via
    person similarity using tensor-based regression,” 第25回 画像の認識・理解シンポジウム (MIRU 2022), 2022. 
  2. 〇叶 穎睿, 諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “知識蒸留を用いたFew-shot Learningに基づく画像の感情ラベル推定に関する検討,” 映像情報メディア学会技術報告, vol. 46, no. 6, pp. 171-175, 2022.2.
  3. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “画像中の物体情報を考慮したユーザ類似度に基づく個人に特化した注視領域の推定に関する検討,” 映像情報メディア学会技術報告, vol. 44, no. 6, pp. 181－186, 2022.2.
  4. 〇叶 穎睿, 諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “Few-shot learningを用いた感情ラベル推定における複数のデータセット利用に関する初期検討,” 令和3年度電気・情報関係学会北海道支部連合大会, pp. 123-124, 2021.11.
  5. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “路面画像を用いた異常検知に基づく路面状態の識別に関する検討,” 令和2年度電気・情報関係学会北海道支部連合大会, pp. 118-119, 2020.11.
  6. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “画像注視時のヒトの感情推定のための視線特徴の推定に関する検討,” 映像情報メディア学会技術報告, vol. 44, no. 6, pp. 85-89, 2020.2.
  7. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “Sparse Bayesian Learningに基づく注視領域の時間変化を考慮したヒトの感情推定に関する検討,” 令和元年度電気・情報関係学会北海道支部連合大会, pp. 149-150, 2019.11.
  8. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “視線情報を考慮した画像のテンソル表現に基づく感情ラベル推定に関する検討 –複数ユーザの推定結果の統合に基づく高精度化–,” 第22回 画像の認識・理解シンポジウム (MIRU), pp. 1-4, 2019.7.
  9. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “画像の視覚的および空間的特徴に基づくユーザに特化した注視領域推定の高精度化に関する検討 ～視覚的特徴の類似度と推定精度の関係性に関する一考察～,” イメージ・メディア・クオリティ研究会 (IMQ), pp. 13-16, 2019.7.
  10. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “画像注視時の注視領域の時間変化を考慮したテンソル解析に基づく感情推定に関する検討,” 平成30年度電気・情報関係学会北海道支部連合大会, pp. 137-138, 2018.11.

Lecture

  1. 〇諸戸 祐哉, 前田 圭介, 小川 貴弘, 長谷山 美紀: “［特別講演］路面画像を用いた深層学習に基づく路面状態の識別に関する検討,” 映像情報メディア学会技術報告, vol. 45, no. 4, pp. 165–169, 2021.2.

Research Activities

Review

  • JSNAI 2022

Awards

  1. JEES・Mitsubishi Corporation Science and Technology Scholarship (Mar. 2022)
  2. 2021 IEEE Sapporo Section Student Paper Contest (Feb. 2022, Ye et al.)
  3. The 2021 IEEE Sapporo Section Encouragement Award (Feb. 2022)
  4. 日本学生支援機構 第一種奨学金 特に優れた業績による奨学金返還全学免除 (Jun, 2021)
  5. 電子情報通信学会北海道支部学生奨励賞 (Mar. 2021)
  6. IEEE LifeTech2021 Excellent Poster (On-site) Award Winners: Bronze Prize (Mar. 2021)
  7. 令和2年度 電気・情報関係学会北海道支部連合大会 若手優秀論文発表賞 (Nov. 2020)
  8. JSPS Research Fellow DC1 Accepted (Apr. 2021，Acceptance rate: 20%)
  9. The 2019 IEEE Sapporo Section Student Paper Contest Encouraging Prize (Feb. 2020)
  10. NITORI International Scholarship Foundation’s Scholarship for Future IT Human Resources (Jul. 2020)
  11. 2nd Prize IEEE LifeTech 2019 Excellent Paper Award (Mar. 2019)
  12. IEEE GCCE 2018 Outstanding Paper Award (Oct. 2018)

 

Others

  • 寳金総長に伝えたい！（Jan. 2021） [link]
  • AI Lab リサーチインターンシップ2021に参加してみて（Nov. 2021） [link]

 

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