| A transfer learning method with deep convolutional neural network for diffuse lung disease classification H Shouno, S Suzuki, S Kido Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015 | 34 | 2015 |
| Image pre-transformation for recognition-aware image compression S Suzuki, M Takagi, K Hayase, T Onishi, A Shimizu 2019 IEEE International Conference on Image Processing (ICIP), 2686-2690, 2019 | 17 | 2019 |
| Deep feature compression with spatio-temporal arranging for collaborative intelligence S Suzuki, M Takagi, S Takeda, R Tanida, H Kimata 2020 IEEE International Conference on Image Processing (ICIP), 3099-3103, 2020 | 12 | 2020 |
| Deep feature compression using spatio-temporal arrangement toward collaborative intelligent world S Suzuki, S Takeda, M Takagi, R Tanida, H Kimata, H Shouno IEEE Transactions on Circuits and Systems for Video Technology 32 (6), 3934-3946, 2021 | 11 | 2021 |
| A study on visual interpretation of network in network S Suzuki, H Shouno 2017 International Joint Conference on Neural Networks (IJCNN), 903-910, 2017 | 9 | 2017 |
| A 2-staged transfer learning method with deep convolutional neural network for diffuse lung disease analysis A Suzuki, S Suzuki, S Kido, H Shouno Proceedings of International Forum on Medical Imaging in Asia, 160-163, 2017 | 8 | 2017 |
| On the use of modality-specific large-scale pre-trained encoders for multimodal sentiment analysis A Ando, R Masumura, A Takashima, S Suzuki, N Makishima, K Suzuki, ... 2022 IEEE Spoken Language Technology Workshop (SLT), 739-746, 2023 | 7 | 2023 |
| Support vector machine histogram: New analysis and architecture design method of deep convolutional neural network S Suzuki, H Shouno Neural Processing Letters 47, 767-782, 2018 | 5 | 2018 |
| An architecture design method of deep convolutional neural network S Suzuki, H Shouno Neural Information Processing: 23rd International Conference, ICONIP 2016 …, 2016 | 5 | 2016 |
| Measuring shift-invariance of convolutional neural network with a probability-incorporated metric H Higuchi, S Suzuki, H Shouno Neural Information Processing: 28th International Conference, ICONIP 2021 …, 2021 | 3 | 2021 |
| ディプラニングの医用画像への応用 庄野逸， 鈴木聡志， 木戸尚治 医用画像情報学会雑誌 33 (4), 75-80, 2016 | 3 | 2016 |
| Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff S Suzuki, S Yamaguchi, S Takeda, S Kanai, N Makishima, A Ando, ... International Conference on Computer Vision (ICCV), 2023 | 2 | 2023 |
| Speaker consistency loss and step-wise optimization for semi-supervised joint training of TTS and ASR using unpaired text data N Makishima, S Suzuki, A Ando, R Masumura arXiv preprint arXiv:2207.04659, 2022 | 2 | 2022 |
| Knowledge Transferred Fine-Tuning: Convolutional Neural Network Is Born Again With Anti-Aliasing Even in Data-Limited Situations S Suzuki, S Takeda, N Makishima, A Ando, R Masumura, H Shouno IEEE Access 10, 68384-68396, 2022 | 2 | 2022 |
| Customer satisfaction estimation using unsupervised representation learning with multi-format prediction loss A Ando, Y Murata, R Masumura, S Suzuki, N Makishima, T Moriya, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 2 | 2022 |
| Knowledge transferred fine-tuning for anti-aliased convolutional neural network in data-limited situation S Suzuki, S Takeda, R Tanida, H Kimata, H Shouno 2021 IEEE International Conference on Image Processing (ICIP), 864-868, 2021 | 2 | 2021 |
| Architecture design of deep convolutional neural network for diffuse lung disease using representation separation information S Suzuki, N Iida, H Shouno, S Kido Proceedings of the International Conference on Parallel and Distributed …, 2016 | 2 | 2016 |
| びまん性肺疾患識別における Deep Convolutional Neural Network 特徴の解析 鈴木聡志， 庄野逸， 木戸尚治 研究報告バイオ情報学 (BIO) 2015 (29), 1-6, 2015 | 2* | 2015 |
| Deep Convolutional Neural Network を用いたびまん性肺疾患画像の特徴解析 鈴木聡志， 庄野逸， 木戸尚治 電子情報通信学会技術研究報告; 信学技報 114 (515), 259-264, 2015 | 2 | 2015 |
| Distorted image classification using neural activation pattern matching loss S Suzuki, S Takeda, R Tanida, Y Bandoh, H Shouno Neural Networks 167, 50-64, 2023 | 1 | 2023 |
Shouno HayaruUniversity of Electro-Communications在 uec.ac.jp 的电子邮件经过验证
