| 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 | 112 | 2018 |
| Overview of the 7th workshop on Asian translation T Nakazawa, H Nakayama, C Ding, R Dabre, S Higashiyama, H Mino, ... Proceedings of the 7th Workshop on Asian Translation, 1-44, 2020 | 93 | 2020 |
| Compressing Word Embeddings via Deep Compositional Code Learning R Shu, H Nakayama International Conference for Learning Representations (ICLR), 2018 | 82 | 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 | 69 | 2010 |
| 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 | 64 | 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 | 58 | 2019 |
| 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 | 57 | 2016 |
| Multimodal gesture recognition using multi-stream recurrent neural network N Nishida, H Nakayama Image and Video Technology, 682-694, 2015 | 57 | 2015 |
| 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 | 49 | 2019 |
| 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 | 46 | 2007 |
| 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 | 44 | 2019 |
| 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 | 43* | 2015 |
| Zero-resource machine translation by multimodal encoder–decoder network with multimedia pivot H Nakayama, N Nishida Machine Translation 31 (1), 49-64, 2017 | 38 | 2017 |
| 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 | 34 | 2020 |
| 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 | 34 | 2019 |
| Semantic Aware Attention Based Deep Object Co-segmentation H Chen, Y Huang, H Nakayama Proceedings of Asian Conference on Computer Vision (ACCV), 2018 | 34 | 2018 |
| 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 | 30 | 2015 |
| Improving local descriptors by embedding global and local spatial information T Harada, H Nakayama, Y Kuniyoshi European Conference on Computer Vision, 736-749, 2010 | 30 | 2010 |
| 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 | 29 | 2020 |
| Faster autoaugment: Learning augmentation strategies using backpropagation R Hataya, J Zdenek, K Yoshizoe, H Nakayama European Conference on Computer Vision, 1-16, 2020 | 27 | 2020 |
Tatsuya HaradaThe University of Tokyo確認したメール アドレス: mi.t.u-tokyo.ac.jp
