ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Generation of Multiple-Depth 3D Computer-Generated Holograms from 2D-Image-Datasets Trained CNN.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- CD8a + GZMK + T Cells Inhibit Osteoclastogenesis in Postmenopausal Osteoporosis via the p38-MAPK Pathway.Calcified tissue international · 2025Article
- Review
- Generation of Multiple-Depth 3D Computer-Generated Holograms from 2D-Image-Datasets Trained CNN.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
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Authors and funding
11 authors.
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Abstract
Generating computer-generated holograms (CGHs) for 3D scenes by learning-based methods can reconstruct arbitrary 3D scenes with higher quality and faster speed. However, the homogenization and difficulty of obtaining 3D high-resolution datasets seriously limit the generalization ability of the model. A novel approach is proposed to train 3D encoding models based on convolutional neural networks (CNNs) using 2D image datasets. This technique produces virtual depth (VD) images with a statistically uniform distribution. This approach employs a CNN trained with the angular spectrum method (ASM) for calculating diffraction fields layer by layer. A fully convolutional neural network architecture for phase-only encoding, which is trained on the DIV2K-VD dataset. Experimental results validate its effectiveness by generating a 4K phase-only hologram within only 0.061 s, yielding high-quality holograms that have an average PSNR of 34.7 dB along with an SSIM of 0.836, offering high quality, economic and time efficiencies compared to traditional methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.