Hideki Nakayama
Hideki Nakayama
The University of Tokyo, Associate Professor
Verified email at ci.i.u-tokyo.ac.jp - Homepage
Title
Cited by
Cited by
Year
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
682018
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
652010
Compressing Word Embeddings via Deep Compositional Code Learning
R Shu, H Nakayama
International Conference for Learning Representations (ICLR), 2018
612018
Multimodal gesture recognition using multi-stream recurrent neural network
N Nishida, H Nakayama
Image and Video Technology, 682-694, 2015
532015
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
492016
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
432018
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
412007
Zero-resource machine translation by multimodal encoder–decoder network with multimedia pivot
H Nakayama, N Nishida
Machine Translation 31 (1-2), 49-64, 2017
352017
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
292019
Improving local descriptors by embedding global and local spatial information
T Harada, H Nakayama, Y Kuniyoshi
European Conference on Computer Vision, 736-749, 2010
292010
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
282019
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
262015
深層畳み込みニューラルネットワークによる画像特徴抽出と転移学習
中山英樹
信学技報 115 (146), 55-59, 2015
262015
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
252013
Linear distance metric Learning for large-scale generic image recognition
H Nakayama
PhD thesis, The University of Tokyo, Japan, 2011
242011
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
232019
Semantic Aware Attention Based Deep Object Co-segmentation
H Chen, Y Huang, H Nakayama
Proceedings of Asian Conference on Computer Vision (ACCV), 2018
212018
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
202010
Ai goggles: Real-time description and retrieval in the real world with online learning
H Nakayama, T Harada, Y Kuniyoshi
2009 Canadian Conference on Computer and Robot Vision, 184-191, 2009
202009
Evaluation of dimensionality reduction methods for image auto-annotation
H Nakayama, T Harada, Y Kuniyoshi
British Machine Vision Conference (BMVC), 2010
192010
The system can't perform the operation now. Try again later.
Articles 1–20