Hideki Nakayama
Hideki Nakayama
The University of Tokyo, Associate Professor
Verified email at ci.i.u-tokyo.ac.jp - 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
Compressing Word Embeddings via Deep Compositional Code Learning
R Shu, H Nakayama
International Conference for Learning Representations (ICLR), 2018
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
Multimodal gesture recognition using multi-stream recurrent neural network
N Nishida, H Nakayama
Image and Video Technology, 682-694, 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
Deep learning for forecasting stock returns in the cross-section
M Abe, H Nakayama
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 273-284, 2018
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
Zero-resource machine translation by multimodal encoder–decoder network with multimedia pivot
H Nakayama, N Nishida
Machine Translation 31 (1-2), 49-64, 2017
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
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
Improving local descriptors by embedding global and local spatial information
T Harada, H Nakayama, Y Kuniyoshi
European Conference on Computer Vision, 736-749, 2010
Image-mediated learning for zero-shot cross-lingual document retrieval
R Funaki, H Nakayama
Proceedings of the 2015 Conference on Empirical Methods in Natural Language …, 2015
信学技報 115 (146), 55-59, 2015
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
Semantic Aware Attention Based Deep Object Co-segmentation
H Chen, Y Huang, H Nakayama
Proceedings of Asian Conference on Computer Vision (ACCV), 2018
Correspondence learning apparatus and method and correspondence learning program, annotation apparatus and method and annotation program, and retrieval apparatus and method and …
T Harada, H Nakayama, R Matsumoto, Y Kuniyoshi, N Otsu
US Patent 8,423,485, 2013
Linear distance metric Learning for large-scale generic image recognition
H Nakayama
PhD thesis, The University of Tokyo, Japan, 2011
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
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
High-speed 3D object recognition using additive features in a linear subspace.
A Kanezaki, H Nakayama, T Harada, Y Kuniyoshi
IEEE International Conference on Robotics and Automation (ICRA), 3128-3134, 2010
The system can't perform the operation now. Try again later.
Articles 1–20