| 2026 | LREC | A Japanese Dataset for Aspect-based Sentiment Polarity Classification and Emotion Intensity Estimation. | Kentaro Hanafusa, Kota Manabe, Yuki Maeda, Daisuke Maekawa, Tomoyuki Kajiwara, Hideaki Hayashi, Yuta Nakashima, Hajime Nagahara |
| 2025 | ICLR | Gaussian-Based Instance-Adaptive Intensity Modeling for Point-Supervised Facial Expression Spotting. | Yicheng Deng, Hideaki Hayashi, Hajime Nagahara |
| 2025 | WACV | Multi-task Learning of Classification and Generation for Set-structured Data. | Fumioki Sato, Hideaki Hayashi, Hajime Nagahara |
| 2024 | ICANN | CALICO: Confident Active Learning with Integrated Calibration. | Lorenzo S. Querol, Hajime Nagahara, Hideaki Hayashi |
| 2024 | ICCE | Is Internal State Feedback in an E-Learning Environment Acceptable to People? | Atsushi Ashida, Ryosuke Kawamura, Shizuka Shirai, Noriko Takemura, Mehrasa Alizadeh, Hideaki Hayashi, Hajime Nagahara |
| 2024 | IJCNN | Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model. | Masahito Toba, Seiichi Uchida, Hideaki Hayashi |
| 2024 | WACV | MIDAS: Mixing Ambiguous Data with Soft Labels for Dynamic Facial Expression Recognition. | Ryosuke Kawamura, Hideaki Hayashi, Noriko Takemura, Hajime Nagahara |
| 2023 | ICDAR | Analyzing Font Style Usage and Contextual Factors in Real Images. | Naoya Yasukochi, Hideaki Hayashi, Daichi Haraguchi, Seiichi Uchida |
| 2021 | ICASSP | Layer-Wise Interpretation of Deep Neural Networks using Identity Initialization. | Shohei Kubota, Hideaki Hayashi, Tomohiro Hayase, Seiichi Uchida |
| 2021 | ICDAR | Meta-learning of Pooling Layers for Character Recognition. | Takato Otsuzuki, Heon Song, Seiichi Uchida, Hideaki Hayashi |
| 2021 | ICLR | A Discriminative Gaussian Mixture Model with Sparsity. | Hideaki Hayashi, Seiichi Uchida |
| 2021 | MICCAI | Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels. | Shota Harada, Ryoma Bise, Hideaki Hayashi, Kiyohito Tanaka, Seiichi Uchida |
| 2020 | ICANN | Regularized Pooling. | Takato Otsuzuki, Hideaki Hayashi, Yuchen Zheng, Seiichi Uchida |
| 2020 | ICFHR | Handwriting Prediction Considering Inter-Class Bifurcation Structures. | Masaki Yamagata, Hideaki Hayashi, Seiichi Uchida |
| 2019 | ICDAR | Page Segmentation using a Convolutional Neural Network with Trainable Co-Occurrence Features. | Joonho Lee, Hideaki Hayashi, Wataru Ohyama, Seiichi Uchida |
| 2019 | ICDAR | Modality Conversion of Handwritten Patterns by Cross Variational Autoencoders. | Taichi Sumi, Brian Kenji Iwana, Hideaki Hayashi, Seiichi Uchida |
| 2019 | MICCAI | Efficient Soft-Constrained Clustering for Group-Based Labeling. | Ryoma Bise, Kentaro Abe, Hideaki Hayashi, Kiyohito Tanaka, Seiichi Uchida |
| 2018 | ACCV | A Trainable Multiplication Layer for Auto-correlation and Co-occurrence Extraction. | Hideaki Hayashi, Seiichi Uchida |
| 2017 | PSIVT | Globally Optimal Object Tracking with Complementary Use of Single Shot Multibox Detector and Fully Convolutional Network. | Jinho Lee, Brian Kenji Iwana, Shouta Ide, Hideaki Hayashi, Seiichi Uchida |