Electrostatic Precipitators for Cleaning Diesel Exhaust. - Hiroshi Umemoto; Hideaki Hayashi; Kazunori Takashima; Akira Mizuno (IAS, 2008)

Electrostatic Charging and Precipitation of Diesel Soot. - Hideaki Hayashi; Yasuhiro Takasaki; Kazuki Kawahara; Tomoya Takenaka; Kazunori Takashima; Akira Mizuno; Moo Been Chang (IAS, 2009)

Collection of Diesel Exhaust Particle Using Gradient Force. - Hideaki Hayashi; Kazunori Takashima; Akira Mizuno (IAS, 2010)

Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis. - Hideaki Hayashi; Keisuke Shima; Taro Shibanoki; Yuichi Kurita; Toshio Tsuji (EMBC, 2013)

Regeneration of diesel particulate filter using sliding discharge. - Ryuichi Seiyama; Takashi Yamaji; Hideaki Hayashi; Kazunori Takashima; Akira Mizuno (IAS, 2013)

A non-Gaussian approach for biosignal classification based on the Johnson SU translation system. - Hideaki Hayashi; Yuichi Kurita; Toshio Tsuji (IWCIA, 2015)

A neural network based infant monitoring system to facilitate diagnosis of epileptic seizures. - Yuya Ogura; Hideaki Hayashi; Shota Nakashima; Zu Soh; Taro Shibanoki; Koji Shimatani; Akihito Takeuchi; Makoto Nakamura; Akihisa Okumura; Yuichi Kurita; Toshio Tsuji (EMBC, 2015)

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis. - Hideaki Hayashi; Taro Shibanoki; Keisuke Shima; Yuichi Kurita; Toshio Tsuji (IEEE Trans. Neural Networks Learn. Syst., 2015)

Variance distribution analysis of surface EMG signals based on marginal maximum likelihood estimation. - Akira Furui; Hideaki Hayashi; Yuichi Kurita; Toshio Tsuji (EMBC, 2017)

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 (PSIVT, 2017)

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution. - Hideaki Hayashi; Akira Furui; Yuichi Kurita; Toshio Tsuji (IEEE Trans. Biomed. Eng., 2017)

A Trainable Multiplication Layer for Auto-correlation and Co-occurrence Extraction. - Hideaki Hayashi; Seiichi Uchida (ACCV (2), 2018)

Biosignal Data Augmentation Based on Generative Adversarial Networks. - Shota Harada; Hideaki Hayashi; Seiichi Uchida (EMBC, 2018)

GAN-based synthetic brain MR image generation. - Changhee Han; Hideaki Hayashi; Leonardo Rundo; Ryosuke Araki; Wataru Shimoda; Shinichi Muramatsu; Yujiro Furukawa; Giancarlo Mauri; Hideki Nakayama (ISBI, 2018)

Endoscopic Image Clustering with Temporal Ordering Information Based on Dynamic Programming. - Shota Harada; Hideaki Hayashi; Ryoma Bise; Kiyohito Tanaka; Qier Meng; Seiichi Uchida (EMBC, 2019)

Page Segmentation using a Convolutional Neural Network with Trainable Co-Occurrence Features. - Joonho Lee; Hideaki Hayashi; Wataru Ohyama; Seiichi Uchida (ICDAR, 2019)

Modality Conversion of Handwritten Patterns by Cross Variational Autoencoders. - Taichi Sumi; Brian Kenji Iwana; Hideaki Hayashi; Seiichi Uchida (ICDAR, 2019)

Efficient Soft-Constrained Clustering for Group-Based Labeling. - Ryoma Bise; Kentaro Abe; Hideaki Hayashi; Kiyohito Tanaka; Seiichi Uchida (MICCAI (5), 2019)

Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection. - Changhee Han; Leonardo Rundo; Ryosuke Araki; Yudai Nagano; Yujiro Furukawa; Giancarlo Mauri; Hideki Nakayama; Hideaki Hayashi (IEEE Access, 2019)

Biosignal Generation and Latent Variable Analysis With Recurrent Generative Adversarial Networks. - Shota Harada; Hideaki Hayashi; Seiichi Uchida (IEEE Access, 2019)

Infinite Brain MR Images: PGGAN-based Data Augmentation for Tumor Detection. - Changhee Han; Leonardo Rundo; Ryosuke Araki; Yujiro Furukawa; Giancarlo Mauri; Hideki Nakayama; Hideaki Hayashi (CoRR, 2019)

ProbAct: A Probabilistic Activation Function for Deep Neural Networks. - Joonho Lee; Kumar Shridhar; Hideaki Hayashi; Brian Kenji Iwana; Seokjun Kang; Seiichi Uchida (CoRR, 2019)

SDGM: Sparse Bayesian Classifier Based on a Discriminative Gaussian Mixture Model. - Hideaki Hayashi; Seiichi Uchida (CoRR, 2019)

GlyphGAN: Style-consistent font generation based on generative adversarial networks. - Hideaki Hayashi; Kohtaro Abe; Seiichi Uchida (Knowl. Based Syst., 2019)

A Scale Mixture-Based Stochastic Model of Surface EMG Signals With Variable Variances. - Akira Furui; Hideaki Hayashi; Toshio Tsuji (IEEE Trans. Biomed. Eng., 2019)

Regularized Pooling. - Takato Otsuzuki; Hideaki Hayashi; Yuchen Zheng; Seiichi Uchida (ICANN (2), 2020)

Handwriting Prediction Considering Inter-Class Bifurcation Structures. - Masaki Yamagata; Hideaki Hayashi; Seiichi Uchida (ICFHR, 2020)

Infinite Brain MR Images: PGGAN-Based Data Augmentation for Tumor Detection. - Changhee Han; Leonardo Rundo; Ryosuke Araki; Yujiro Furukawa; Giancarlo Mauri; Hideki Nakayama; Hideaki Hayashi (Neural Approaches to Dynamics of Signal Exchanges, 2020)

Layer-Wise Interpretation of Deep Neural Networks using Identity Initialization. - Shohei Kubota; Hideaki Hayashi; Tomohiro Hayase; Seiichi Uchida (ICASSP, 2021)

Meta-learning of Pooling Layers for Character Recognition. - Takato Otsuzuki; Heon Song; Seiichi Uchida; Hideaki Hayashi (ICDAR (3), 2021)

A Discriminative Gaussian Mixture Model with Sparsity. - Hideaki Hayashi; Seiichi Uchida (ICLR, 2021)

Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels. - Shota Harada; Ryoma Bise; Hideaki Hayashi; Kiyohito Tanaka; Seiichi Uchida (MICCAI (2), 2021)

A Neural Network Based on the Johnson SU Translation System and Related Application to Electromyogram Classification. - Hideaki Hayashi; Taro Shibanoki; Toshio Tsuji (IEEE Access, 2021)

Soft and self constrained clustering for group-based labeling. - Shota Harada; Ryoma Bise; Hideaki Hayashi; Kiyohito Tanaka; Seiichi Uchida (Medical Image Anal., 2021)

Deep Bayesian Active-Learning-to-Rank for Endoscopic Image Data. - Takeaki Kadota; Hideaki Hayashi; Ryoma Bise; Kiyohito Tanaka; Seiichi Uchida (MIUA, 2022)

Analyzing Font Style Usage and Contextual Factors in Real Images. - Naoya Yasukochi; Hideaki Hayashi; Daichi Haraguchi; Seiichi Uchida (ICDAR (3), 2023)

Multi-Scale Spatio-Temporal Graph Convolutional Network for Facial Expression Spotting. - Yicheng Deng; Hideaki Hayashi; Hajime Nagahara (FG, 2024)

CALICO: Confident Active Learning with Integrated Calibration. - Lorenzo S. Querol; Hajime Nagahara; Hideaki Hayashi (ICANN (1), 2024)

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 (ICCE, 2024)

Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model. - Masahito Toba; Seiichi Uchida; Hideaki Hayashi (IJCNN, 2024)

MIDAS: Mixing Ambiguous Data with Soft Labels for Dynamic Facial Expression Recognition. - Ryosuke Kawamura; Hideaki Hayashi; Noriko Takemura; Hajime Nagahara (WACV, 2024)

Exploiting SRv6 for Stateless and Per-Connection-Consistent Load Balancing. - Ryo Nakamura; Kentaro Ebisawa; Hideaki Hayashi; Tatsuya Fujiwara; Tomoko Okuzawa (IEEE Access, 2024)

SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spotting. - Yicheng Deng; Hideaki Hayashi; Hajime Nagahara (CoRR, 2024)

Deep Bayesian active learning-to-rank with relative annotation for estimation of ulcerative colitis severity. - Takeaki Kadota; Hideaki Hayashi; Ryoma Bise; Kiyohito Tanaka; Seiichi Uchida (Medical Image Anal., 2024)

Gaussian-Based Instance-Adaptive Intensity Modeling for Point-Supervised Facial Expression Spotting. - Yicheng Deng; Hideaki Hayashi; Hajime Nagahara (ICLR, 2025)

Discriminative Analysis of Autistic Tendencies at 18 Months of Age Using Eye Gaze Characteristics in 4-, 10-, and 18-month-old Infants. - Rena Ueda; Hirokazu Doi; Akira Furui; Koji Shimatani; Hideaki Hayashi; Toshio Tsuji (SII, 2025)

Non-Negative Tensor Factorization of Infant Spontaneous Movements: A Pilot Study for ASD Risk Evaluation of Newborn Infants. - Rikuya Yonei; Akira Furui; Hirokazu Doi; Koji Shimatani; Hideaki Hayashi; Midori Yamamoto; Kenichi Sakurai; Chisato Mori; Toshio Tsuji (SII, 2025)

Multi-task Learning of Classification and Generation for Set-structured Data. - Fumioki Sato; Hideaki Hayashi; Hajime Nagahara (WACV, 2025)

A Hybrid of Generative and Discriminative Models Based on the Gaussian-Coupled Softmax Layer. - Hideaki Hayashi (IEEE Trans. Neural Networks Learn. Syst., 2025)

Enhancing Ambiguous Dynamic Facial Expression Recognition with Soft Label-based Data Augmentation. - Ryosuke Kawamura; Hideaki Hayashi; Shunsuke Otake; Noriko Takemura; Hajime Nagahara (CoRR, 2025)