most citedHyperparameter tuning of optical neural network classifiers for high-order gaussian beams

20 citations · 61 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20212 cited

Image quality enhancement of embedded holograms in holographic information hiding using deep neural networks

Tomoyoshi Shimobaba, Sota Oshima, Takashi Kakue +1

Holographic information hiding is a technique for embedding holograms or images into another hologram, used for copyright protection and steganography of holograms. Using deep neur…

physics.optics202120 cited

Hyperparameter tuning of optical neural network classifiers for high-order gaussian beams

Shunsuke Watanabe, Tomoyoshi Shimobaba, Takashi Kakue +1

High-order Gaussian beams with multiple propagation modes have been studied for free-space optical communications. Fast classification of beams using a diffractive deep neural netw…

cs.CV202120 cited

Optimization of phase-only holograms calculated with scaled diffraction calculation through deep neural networks

Yoshiyuki Ishii, Tomoyoshi Shimobaba, David Blinder +4

Computer-generated holograms (CGHs) are used in holographic three-dimensional (3D) displays and holographic projections. The quality of the reconstructed images using phase-only CG…

physics.optics201411 cited

Numerical investigation of lensless zoomable holographic multiple projections to tilted planes

Tomoyoshi Shimobaba, Michal Makowski, Takashi Kakue +7

This paper numerically investigates the feasibility of lensless zoomable holographic multiple projections to tilted planes. We have already developed lensless zoomable holographic…

physics.optics20148 cited

Ptychography by changing the area of probe light and scaled ptychography

Tomoyoshi Shimobaba, Takashi Kakue, Naohisa Okada +4

Ptychography is a promising phase retrieval technique for visible light, X-ray and electron beams. Conventional ptychography reconstructs the amplitude and phase of an object light…