Segui
HAYASHI, Hideaki
HAYASHI, Hideaki
Email verificata su ids.osaka-u.ac.jp - Home page
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Citata da
Citata da
Anno
GAN-based synthetic brain MR image generation
C Han, H Hayashi, L Rundo, R Araki, W Shimoda, S Muramatsu, ...
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
3752018
Combining noise-to-image and image-to-image GANs: Brain MR image augmentation for tumor detection
C Han, L Rundo, R Araki, Y Nagano, Y Furukawa, G Mauri, H Nakayama, ...
IEEE Access 7, 156966-156977, 2019
1952019
Biosignal Data Augmentation Based on Generative Adversarial Networks
S Harada, H Hayashi, S Uchida
40th Annual International Conference of the IEEE Engineering in Medicine and …, 2018
1292018
Infinite Brain MR Images: PGGAN-based Data Augmentation for Tumor Detection
C Han, L Rundo, R Araki, Y Furukawa, G Mauri, H Nakayama, H Hayashi
Smart Innovation, System and Technologies, 2018
1012018
GlyphGAN: Style-Consistent Font Generation Based on Generative Adversarial Networks
H Hayashi, K Abe, S Uchida
Knowledge-Based Systems, 2019
602019
Markerless Measurement and evaluation of General Movements in infants
T Tsuji, S Nakashima, H Hayashi, Z Soh, A Furui, T Shibanoki, K Shima, ...
Scientific reports 10 (1), 1-13, 2020
482020
ProbAct: A Probabilistic Activation Function for Deep Neural Networks
J Lee, K Shridhar, H Hayashi, BK Iwana, S Kang, S Uchida
arXiv preprint arXiv:1905.10761, 2019
432019
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis
H Hayashi, T Shibanoki, K Shima, Y Kurita, T Tsuji
Neural Networks and Learning Systems, IEEE Transactions on 26 (12), 3021-3033, 2015
342015
Biosignal Generation and Latent Variable Analysis with Recurrent Generative Adversarial Networks
S Harada, H Hayashi, S Uchida
IEEE Access 7, 144292-144302, 2019
312019
Predicting ischemic stroke after carotid artery stenting based on proximal calcification and the jellyfish sign
N Ichinose, S Hama, T Tsuji, Z Soh, H Hayashi, Y Kiura, S Sakamoto, ...
Journal of neurosurgery 128 (5), 1280-1288, 2018
292018
Page Segmentation using a Convolutional Neural Network with Trainable Co-occurrence Features
J Lee, H Hayashi, W Ohyama, S Uchida
Proceedings of The 15th International Conference on Document Analysis and …, 2019
282019
A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution
H Hayashi, A Furui, Y Kurita, T Tsuji
IEEE Transactions on Biomedical Engineering 64 (11), 2672-2681, 2017
232017
An artificial EMG generation model based on signal-dependent noise and related application to motion classification
A Furui, H Hayashi, G Nakamura, T Chin, T Tsuji
PloS one 12 (6), e0180112, 2017
182017
A scale mixture-based stochastic model of surface EMG signals with variable variances
A Furui, H Hayashi, T Tsuji
IEEE Transactions on Biomedical Engineering 66 (10), 2780-2788, 2019
142019
Modality Conversion of Handwritten Patterns by Cross Variational Autoencoders
T Sumi, BK Iwana, H Hayashi, S Uchida
Proceedings of The 15th International Conference on Document Analysis and …, 2019
132019
Efficient Soft-Constrained Clustering for Group-Based Labeling
R Bise, K Abe, H Hayashi, K Tanaka, S Uchida
Proceedings of The 22nd International Conference on Medical Image Computing …, 2019
92019
Human–Machine Interfaces Based on Bioelectric Signals: A Narrative Review with a Novel System Proposal
H Hayashi, T Tsuji
IEEJ Transactions on Electrical and Electronic Engineering, 2022
82022
Regularized Pooling
T Otsuzuki, H Hayashi, Y Zheng, S Uchida
The 29th International Conference on Artificial Neural Networks (ICANN 2020), 2020
82020
A Neural Network Based Infant Monitoring System to Facilitate Diagnosis of Epileptic Seizures
Y Ogura, H Hayashi, S Nakashima, Z Soh, ...
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual …, 2015
72015
A Discriminative Gaussian Mixture Model with Sparsity
H Hayashi, S Uchida
The 9th International Conference on Learning Representations (ICLR 2021 …, 2021
6*2021
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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