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Ikuo Hoshi

Observed name: I. Hoshi
ORCID: 0000-0003-4783-3491
Observed ORCID: 0000-0003-4783-3491
OpenAlex ID: A5020154976
Deep-Learning Computational Holography: A Review
2022 · Tomoyoshi Shimobaba, David Blinder, et al. · Frontiers in Photonics · 97
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Single-pixel imaging using a recurrent neural network combined with convolutional layers
2020 · Ikuo Hoshi, Tomoyoshi Shimobaba, et al. · Optics Express · 72
Dynamic-range compression scheme for digital hologram using a deep neural network
2019 · Tomoyoshi Shimobaba, David Blinder, et al. · Optics Letters · 28
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Simple complex amplitude encoding of a phase-only hologram using binarized amplitude
2020 · Tomoyoshi Shimobaba, Takayuki Takahashi, et al. · Journal of Optics · 21
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Real-valued diffraction calculations for computational holography [Invited]
2021 · Tomoyoshi Shimobaba, Tatsuki Tahara, et al. · Applied Optics · 11
Wavefront-aberration-tolerant diffractive deep neural networks using volume holographic optical elements
2025 · Ikuo Hoshi, Koki Wakunami, et al. · Scientific Reports · 10
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Mitigating ringing artifacts in diffraction calculations using average subtractions
2021 · Tomoyoshi Shimobaba, Ikuo Hoshi, et al. · Applied Optics · 10
Computational ghost imaging using a field-programmable gate array
2019 · Ikuo Hoshi, Tomoyoshi Shimobaba, et al. · OSA Continuum · 10
Reducing Computational Complexity and Memory Usage of Iterative Hologram Optimization Using Scaled Diffraction
2020 · Tomoyoshi Shimobaba, Michal Makowski, et al. · Applied Sciences · 9
Hologram generation via Hilbert transform
2020 · Tomoyoshi Shimobaba, Takashi Kakue, et al. · OSA Continuum · 8
Real-time single-pixel imaging using a system on a chip field-programmable gate array
2022 · Ikuo Hoshi, Tomoyoshi Shimobaba, et al. · Scientific Reports · 7
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Optimized Binary Patterns by Gradient Descent for Ghost Imaging
2021 · Ikuo Hoshi, Tomoyoshi Shimobaba, et al. · IEEE Access · 7
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Single-pixel imaging for edge images using deep neural networks
2022 · Ikuo Hoshi, Masaki Takehana, et al. · Applied Optics · 6
Phase retrieval using axial diffraction patterns and a ptychographic iterative engine
2019 · Yoshiya Wagatsuma, Tomoyoshi Shimobaba, et al. · Applied Optics · 6
Deep-Learning-Based Dynamic Range Compression for 3D Scene Hologram
2021 · Tomoyoshi Shimobaba, David Blinder, et al. · Springer proceedings in physics · 5
Deep-learning-assisted Hologram Calculation via Low-Sampling Holograms
2019 · Tomoyoshi Shimobaba, David Blinder, et al. · IIAI International Congress on Advanced Applied Informatics (IIAI-AAI) · 5
High-performance computer system dedicated to ray-wavefront conversion technique aimed to display holograms in real-time
2023 · Tatsuya Maruyama, Yasuyuki Ichihashi, et al. · Optical Engineering · 3
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Motion Parallax Holograms Generated from an Existing Hologram
2021 · Tomoyoshi Shimobaba, Shuhei Katsuyama, et al. · Applied Sciences · 3
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Dedicated processor for hologram calculation using sparse Fourier bases
2020 · Daiki Yasuki, David Blinder, et al. · Applied Optics · 3
Data page classification in holographic memory using binary neural network
2020 · Tomoyoshi Shimobaba, Yota Yamamoto, et al. · IEEE International Conference on Industrial Informatics (INDIN) · 1
Full-colour imaging behind a glass diffuser through a diffractive neural network with multi-wavelength channels
2026 · Ikuo Hoshi, Koki Wakunami, et al. · npj Unconventional Computing
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Single-pixel imaging using deep learning, FPGA, and non-negative matrix factorization
2024 · Tomoyoshi Shimobaba, Ikuo Hoshi, et al. · Optical Design and Testing
Machine learning for the design of two-layer holographic optical elements
2024 · Ikuo Hoshi, Koki Wakunami, et al. · AI and Optical Data Sciences
Special-Purpose Computer for Digital Holography
2023 · Nobuyuki Masuda, Ikuo Hoshi · Springer eBooks
Strategies for the next generation of special-purpose computers for holography
2022 · Tomoyoshi Shimobaba, Takayuki Takahashi, et al. · Holography, Diffractive Optics, and Applications
Works count: 29
Citation count: 322
H-index: 9
I10-index: 8
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