| Single-pixel imaging using a recurrent neural network combined with convolutional layers I Hoshi, T Shimobaba, T Kakue, T Ito Optics Express 28 (23), 34069-34078, 2020 | 47 | 2020 |
| Deep-learning computational holography: A review T Shimobaba, D Blinder, T Birnbaum, I Hoshi, H Shiomi, P Schelkens, ... Frontiers in Photonics 3, 8, 2022 | 46 | 2022 |
| Dynamic-range compression scheme for digital hologram using a deep neural network T Shimobaba, D Blinder, M Makowski, P Schelkens, Y Yamamoto, I Hoshi, ... Optics letters 44 (12), 3038-3041, 2019 | 30 | 2019 |
| Simple complex amplitude encoding of a phase-only hologram using binarized amplitude T Shimobaba, T Takahashi, Y Yamamoto, I Hoshi, A Shiraki, T Kakue, ... Journal of Optics 22 (4), 045703, 2020 | 16 | 2020 |
| Computational ghost imaging using a field-programmable gate array I Hoshi, T Shimobaba, T Kakue, T Ito OSA Continuum 2 (4), 1097-1105, 2019 | 10 | 2019 |
| Real-valued diffraction calculations for computational holography T Shimobaba, T Tahara, I Hoshi, H Shiomi, F Wang, T Hara, T Kakue, T Ito Applied Optics 61 (5), B96-B102, 2022 | 9 | 2022 |
| Mitigating ringing artifacts in diffraction calculations using average subtractions T Shimobaba, I Hoshi, H Shiomi, F Wang, T Hara, T Kakue, T Ito Applied Optics 60 (22), 6393-6399, 2021 | 7 | 2021 |
| Deep-learning-assisted hologram calculation via low-sampling holograms T Shimobaba, D Blinder, P Schelkens, Y Yamamoto, I Hoshi, T Kakue, ... 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI …, 2019 | 7 | 2019 |
| Motion parallax holograms generated from an existing hologram T Shimobaba, S Katsuyama, T Nishitsuji, I Hoshi, H Shiomi, F Wang, ... Applied Sciences 11 (7), 2933, 2021 | 6 | 2021 |
| Reducing computational complexity and memory usage of iterative hologram optimization using scaled diffraction T Shimobaba, M Makowski, T Takahashi, Y Yamamoto, I Hoshi, ... Applied Sciences 10 (3), 1132, 2020 | 6 | 2020 |
| Hologram generation via Hilbert transform T Shimobaba, T Kakue, Y Yamamoto, I Hoshi, H Shiomi, T Nishitsuji, ... OSA Continuum 3 (6), 1498-1503, 2020 | 5 | 2020 |
| Phase retrieval using axial diffraction patterns and a ptychographic iterative engine Y Wagatsuma, T Shimobaba, Y Yamamoto, I Hoshi, T Kakue, T Ito Applied Optics 59 (2), 354-362, 2020 | 5 | 2020 |
| Optimized binary patterns by gradient descent for ghost imaging I Hoshi, T Shimobaba, T Kakue, T Ito IEEE Access 9, 97320-97326, 2021 | 4 | 2021 |
| Deep-Learning-Based Dynamic Range Compression for 3D Scene Hologram T Shimobaba, D Blinder, P Schelkens, Y Yamamoto, I Hoshi, A Shiraki, ... ICOL-2019: Proceedings of the International Conference on Optics and Electro …, 2021 | 3 | 2021 |
| Single-pixel imaging for edge images using deep neural networks I Hoshi, M Takehana, T Shimobaba, T Kakue, T Ito Applied Optics 61 (26), 7793-7797, 2022 | 2 | 2022 |
| High-performance computer system dedicated to ray-wavefront conversion technique aimed to display holograms in real-time T Maruyama, Y Ichihashi, I Hoshi, T Kakue, T Shimobaba, T Ito Optical Engineering 62 (8), 085102-085102, 2023 | 1 | 2023 |
| Real-time single-pixel imaging using a system on a chip field-programmable gate array I Hoshi, T Shimobaba, T Kakue, T Ito Scientific Reports 12 (1), 14097, 2022 | 1 | 2022 |
| Dedicated processor for hologram calculation using sparse Fourier bases D Yasuki, D Blinder, T Shimobaba, Y Yamamoto, I Hoshi, P Schelkens, ... Applied Optics 59 (26), 8029-8037, 2020 | 1 | 2020 |
| Data page classification in holographic memory using binary neural network T Shimobaba, Y Yamamoto, I Hoshi, T Kakue, T Ito 2020 IEEE 18th International Conference on Industrial Informatics (INDIN) 1 …, 2020 | 1 | 2020 |
| Machine learning for the design of two-layer holographic optical elements I Hoshi, K Wakunami, Y Ichihashi, R Oi AI and Optical Data Sciences V 12903, 142-146, 2024 | | 2024 |
