| TU-Net and TDeepLab: Deep Learning-Based Terrain Classification Robust to Illumination Changes, Combining Visible and Thermal Imagery Y Iwashita, K Nakashima, A Stoica, R Kurazume IEEE Conference on Multimedia Information Processing and Retrieval (MIPR …, 2019 | 24 | 2019 |
| Fukuoka datasets for place categorization O Martínez Mozos, K Nakashima, H Jung, Y Iwashita, R Kurazume The International Journal of Robotics Research 38 (5), 507-517, 2019 | 19 | 2019 |
| Learning to Drop Points for LiDAR Scan Synthesis K Nakashima, R Kurazume IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS …, 2021 | 16* | 2021 |
| deeplab-pytorch K Nakashima https://github.com/kazuto1011/deeplab-pytorch, 2018 | 14 | 2018 |
| 2V-Gait: Gait Recognition using 3D LiDAR Robust to Changes in Walking Direction and Measurement Distance J Ahn, K Nakashima, K Yoshino, Y Iwashita, R Kurazume IEEE/SICE International Symposium on System Integration (SII), 602-607, 2022 | 12 | 2022 |
| Feasibility Study of IoRT Platform “Big Sensor Box” R Kurazume, Y Pyo, K Nakashima, A Kawamura, T Tsuji IEEE International Conference on Robotics and Automation (ICRA), 3664-3671, 2017 | 12 | 2017 |
| Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data K Nakashima, Y Iwashita, R Kurazume IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 1256-1266, 2023 | 10 | 2023 |
| MU-Net: Deep Learning-Based Thermal IR Image Estimation From RGB Image Y Iwashita, K Nakashima, S Rafol, A Stoica, R Kurazume IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019 | 10 | 2019 |
| LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models K Nakashima, R Kurazume IEEE International Conference on Robotics and Automation (ICRA), 14724-14731, 2024 | 6 | 2024 |
| Learning geometric and photometric features from panoramic LiDAR scans for outdoor place categorization K Nakashima, H Jung, Y Oto, Y Iwashita, R Kurazume, OM Mozos Advanced Robotics 32 (14), 2018 | 6 | 2018 |
| Previewed reality: Near-future perception system Y Horikawa, A Egashira, K Nakashima, A Kawamura, R Kurazume IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS …, 2017 | 6 | 2017 |
| Virtual IR Sensing for Planetary Rovers: Improved Terrain Classification and Thermal Inertia Estimation Y Iwashita, K Nakashima, J Gatto, S Higa, A Stoica, N Khoo, R Kurazume IEEE Robotics and Automation Letters (RA-L) 5 (4), 6302-6309, 2020 | 4 | 2020 |
| Virtual sensors determined through machine learning Y Iwashita, A Stoica, K Nakashima, R Kurazume, J Torresen World Automation Congress (WAC), 1-5, 2018 | 4 | 2018 |
| Gait Recognition using Identity-Aware Adversarial Data Augmentation K Yoshino, K Nakashima, J Ahn, Y Iwashita, R Kurazume IEEE/SICE International Symposium on System Integration (SII), 596-601, 2022 | 3 | 2022 |
| grad-cam-pytorch K Nakashima https://github.com/kazuto1011/grad-cam-pytorch, 2017 | 3 | 2017 |
| Fourth-person sensing for a service robot K Nakashima, Y Iwashita, P Yoonseok, A Takamine, R Kurazume IEEE International Conference on Sensors, 1110-1113, 2015 | 3 | 2015 |
| Understanding Humanitude Care for Sit-to-stand Motion by Wearable Sensors Q An, A Tanaka, K Nakashima, H Sumioka, M Shiomi, R Kurazume IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1874-1879, 2022 | 2 | 2022 |
| Lifelogging caption generation via fourth-person vision in a human–robot symbiotic environment K Nakashima, Y Iwashita, R Kurazume ROBOMECH Journal 7 (1), 33, 2020 | 2 | 2020 |
| Fast LiDAR Upsampling using Conditional Diffusion Models SEM Helgesen, K Nakashima, J Tørresen, R Kurazume arXiv preprint arXiv:2405.04889, 2024 | 1 | 2024 |
| Learning Viewpoint-Invariant Features for LiDAR-Based Gait Recognition J Ahn, K Nakashima, K Yoshino, Y Iwashita, R Kurazume IEEE Access 11, 129749-129762, 2023 | 1 | 2023 |
Ryo KurazumeProfessor of Computer Science, Kyushu UniversityVerified email at ait.kyushu-u.ac.jp