| A deep 3D residual CNN for false‐positive reduction in pulmonary nodule detection H Jin, Z Li, R Tong, L Lin Medical physics 45 (5), 2097-2107, 2018 | 115 | 2018 |
| Preliminary study of AI-assisted diagnosis using FDG-PET/CT for axillary lymph node metastasis in patients with breast cancer Z Li, K Kitajima, K Hirata, R Togo, J Takenaka, Y Miyoshi, K Kudo, ... EJNMMI research 11, 1-10, 2021 | 23 | 2021 |
| Chronic gastritis classification using gastric X-ray images with a semi-supervised learning method based on tri-training Z Li, R Togo, T Ogawa, M Haseyama Medical & Biological Engineering & Computing 58, 1239-1250, 2020 | 13 | 2020 |
| Learning intra-domain style-invariant representation for unsupervised domain adaptation of semantic segmentation Z Li, R Togo, T Ogawa, M Haseyama Pattern Recognition 132, 108911, 2022 | 11 | 2022 |
| Variational autoencoder based unsupervised domain adaptation for semantic segmentation Z Li, R Togo, T Ogawa, M Haseyama 2020 IEEE International Conference on Image Processing (ICIP), 2426-2430, 2020 | 6 | 2020 |
| Classification of subcellular protein patterns in human cells with transfer learning Z Li, R Togo, T Ogawa, M Haseyama 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech …, 2019 | 6 | 2019 |
| Union-set multi-source model adaptation for semantic segmentation Z Li, R Togo, T Ogawa, M Haseyama European Conference on Computer Vision, 579-595, 2022 | 5 | 2022 |
| Developing technologies for the practical application of deep learning-based distress segmentation in subway tunnel images Z LI, K MAEDA, R TOGO, T OGAWA, M HASEYAMA Intelligence, Informatics and Infrastructure 4 (1), 1-8, 2023 | 3 | 2023 |
| Semi-supervised learning based on tri-training for gastritis classification using gastric X-ray images Z Li, R Togo, T Ogawa, M Haseyama 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2019 | 3 | 2019 |
| Improving Model Adaptation for Semantic Segmentation by Learning Model-Invariant Features with Multiple Source-Domain Models Z Li, R Togo, T Ogawa, M Haseyama 2022 IEEE International Conference on Image Processing (ICIP), 421-425, 2022 | 2 | 2022 |
| Unsupervised domain adaptation for semantic segmentation with symmetric adaptation consistency Z Li, R Togo, T Ogawa, M Haseyama ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 2 | 2020 |
| A note on retrieval of visually similar distress regions in subway tunnel images: Introduction of deep features extracted by semantic segmentation network 李宗曜， 藤後廉， 小川貴弘， 長谷山美紀 電子情報通信学会技術研究報告= IEICE technical report: 信学技報 119 (421), 65-68, 2020 | 2 | 2020 |
| Semantic-aware unpaired image-to-image translation for urban scene images Z Li, R Togo, T Ogawa, M Haseyama ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 1 | 2021 |
| Divergence-Guided Feature Alignment for Cross-Domain Object Detection Z Li, R Togo, T Ogawa, M Haseyama ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | | 2022 |
| Detecting axillary lymph node metastasis of breast cancer with FDG-PET/CT images based on attention mechanism Z Li, R Togo, K Hirata, K Kitajima, J Takenaka, Y Miyoshi, K Kudo, ... ITE Technical Report; ITE Tech. Rep. 45 (4), 33-36, 2021 | | 2021 |
| A note on automatic malignant tumor candidate detection based on a 3D deep residual network with FDG-PET/CT images Z Li, R Togo, T Ogawa, K Hirata, O Manabe, T Shiga, M Haseyama ITE Technical Report; ITE Tech. Rep. 43 (5), 311-314, 2019 | | 2019 |
| A note on multi-source model adaptation for semantic segmentation--Improving adaptation performance by learning model-invariant representation from multiple source models Z Li, R Togo, T Ogawa, M Haseyama IEICE Technical Report; IEICE Tech. Rep., 0 | | |
