“Hologram” Science-Research, December 2021 — summary from Astrophysics Data System and DOAJ

Astrophysics Data System — summary generated by Brevi Assistant

Current display innovations are limited to predicting floating ultra-high interpretation pictures on multiple layers, preventing applications in augmented reality for medical education. High-resolution Spatial Light Modulators can allow increasing the field of sight and display size in CGH. An approach for compressing computer-generated holograms making use of genetic algorithm enhanced quantum-inspired neural network is recommended. The experimental results reveal that the hereditary formula maximized quantuminspired neural network can obtain much better top quality rebuilded pictures than the quantum-inspired neural network while using less learning iterations. We suggest an attention-based deep convolutional neural network for computer produced hologram compression, where a channel interest mechanism is used to both computer system produce hologram compression and restoration. By using focus mechanisms to improve the feature representation capacity of deep convolutional neural networks, we can even more improve the efficiency of the rebuilded computer produced hologram. This paper reported a technique for developing monolithic acoustic holograms with factor to consider of both amplitude and stage modulation, which can be used for multifocal point beam of light created by a single element ultrasonic transducer in the regularity of megahertz array. Both the hydrophone testing and the simulation results showed that the holograms designed by our technique might create beam patterns precisely in the expected position. Computer-generated holograms are used in holographic three-dimensional display screens and holographic forecasts. Deep neural networks directly presume CGHs from input photo data. Vergence and lodging responses of human vision are very vital variables when a 3D picture is observed, and a vergence-accommodation problem causes affective distortion, visual discomfort, and tiredness for an onlooker. The A-R of a team of individuals were determined for a genuine pen and its Denisyuk hologram at different visualization ranges making use of an Nvision K5001 autorefractor.

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DOAJ — summary generated by Brevi Assistant

Abstract Acoustic holograms are the keystone of modern-day acoustics. Optimization techniques that regulate only the phase of an acoustic wave are thought about inferior to approaches that regulate both the amplitude and stage of the wave. We show that in one of the most fundamental instances of enhancing the result amplitude to match the target amplitude; our approach with only phase modulation achieves better efficiency than conventional formula with both amplitude and stage inflection. Abstract in this paper, we present 2 methods for recording a quasi-hologram on the steel surface by femtosecond laser pulses. The recording process is done by revolving the polarization of the laser beam of light by a spatial light or a half-wave plate modulator, so we can regulate the spatial positioning of the formed laser-induced periodic surface frameworks. For the first time to our understanding, we managed to record a hologram of a bitmap image by continuously changing the laser beam polarization by SLM during scanning. Vergence and lodging responses of human vision are extremely crucial aspects when a 3D image is observed, and a vergence-accommodation problem creates affective distortion, aesthetic discomfort, and exhaustion for a viewer. The A-R of a group of participants were measured for an actual marker and its Denisyuk hologram at numerous visualization ranges utilizing an Nvision K5001 autorefractor. The experimental results statistically validated the equivalence of the responses to the Denisyuk hologram and its real counterpart, along with the lack of a VAC.

Please keep in mind that the text is machine-generated by the Brevi Technologies’ Natural language Generation model, and we do not bear any responsibility. The text above has not been edited and/or modified in any way.

Source texts:

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