Hideki Nakayama
Hideki Nakayama
The University of Tokyo, Full Professor
Verified email at - Homepage
Cited by
Cited by
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
USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
L Rundo, C Han, Y Nagano, J Zhang, R Hataya, C Militello, A Tangherloni, ...
Neurocomputing 365, 31-43, 2019
Faster autoaugment: Learning augmentation strategies using backpropagation
R Hataya, J Zdenek, K Yoshizoe, H Nakayama
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
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
Overview of the 8th workshop on Asian translation
T Nakazawa, H Nakayama, C Ding, R Dabre, S Higashiyama, H Mino, ...
Proceedings of the 8th Workshop on Asian Translation, Bangkok, Thailand …, 2021
MADGAN: Unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction
C Han, L Rundo, K Murao, T Noguchi, Y Shimahara, ZÁ Milacski, ...
BMC bioinformatics 22, 1-20, 2021
Semantic Aware Attention Based Deep Object Co-segmentation
H Chen, Y Huang, H Nakayama
Proceedings of Asian Conference on Computer Vision (ACCV), 2018
Compressing Word Embeddings via Deep Compositional Code Learning
R Shu, H Nakayama
International Conference for Learning Representations (ICLR), 2018
Deep learning for forecasting stock returns in the cross-section
M Abe, H Nakayama
Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia …, 2018
Learning more with less: Conditional PGGAN-based data augmentation for brain metastases detection using highly-rough annotation on MR images
C Han, K Murao, T Noguchi, Y Kawata, F Uchiyama, L Rundo, ...
Proceedings of the 28th ACM international conference on information and …, 2019
Synthesizing diverse lung nodules wherever massively: 3D multi-conditional GAN-based CT image augmentation for object detection
C Han, Y Kitamura, A Kudo, A Ichinose, L Rundo, Y Furukawa, ...
2019 International Conference on 3D Vision (3DV), 729-737, 2019
Latent-variable non-autoregressive neural machine translation with deterministic inference using a delta posterior
R Shu, J Lee, H Nakayama, K Cho
Proceedings of the aaai conference on artificial intelligence 34 (05), 8846-8853, 2020
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
Neural approaches to dynamics of signal exchanges, 291-303, 2020
信学技報 115 (146), 55-59, 2015
Annotation order matters: Recurrent image annotator for arbitrary length image tagging
J Jin, H Nakayama
2016 23rd international conference on pattern recognition (ICPR), 2452-2457, 2016
Multimodal gesture recognition using multi-stream recurrent neural network
N Nishida, H Nakayama
Image and Video Technology: 7th Pacific-Rim Symposium, PSIVT 2015, Auckland …, 2016
Zero-resource machine translation by multimodal encoder–decoder network with multimedia pivot
H Nakayama, N Nishida
Machine Translation 31, 49-64, 2017
Global Gaussian approach for scene categorization using information geometry
H Nakayama, T Harada, Y Kuniyoshi
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
Journalist robot: Robot system making news articles from real world
R Matsumoto, H Nakayama, T Harada, Y Kuniyoshi
2007 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2007
Meta approach to data augmentation optimization
R Hataya, J Zdenek, K Yoshizoe, H Nakayama
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022
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