.png){kind=icon}
返回
Advancing computer-generated holographic display thanks to diffraction model-driven deep nets
.png){kind=icon}
OA
AI
DOI：10.29026/oea.2024.230176.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Advancements are reported in computer-generated holography proofing RGB 4K display through a new strategy based on diffraction model-driven deep networks. In the new 4K-DMDNet, the network is not a black box anymore. Rather, the input-output relation must obey to the physics of wavefront propagation, which is embedded here as a constraint. Thus, a labelled dataset is not required, and the model shows superior generalization capabilities with respect to data-driven ap-proaches. The method is promising for the new generation of RGB 4K holographic display, as well as augmented and vir-tual reality systems.
Keyword:
PHASE
IMAGE
期刊
IF:
22.4
论文数:
413
被引数:
3.6K
机构
引用论文
Characterization and mobilization of toxic metals from electrolytic zinc waste电解锌废料中有毒金属的表征和动员.png)
Chemosphere
ChemosphereIF0
PREAI
分享收藏
4K-DMDNet: diffraction model-driven network for 4K computer-generated holography4K-DMDNet: 用于4k计算机生成全息的衍射模型驱动网络OPTO-ELECTRONIC ADVANCESOAAI
OPTO-ELECTRONIC ADVANCESIF22.4
OAAI分享收藏High-speed computer-generated holography using an autoencoder-based deep neural network使用基于自动编码器的深度神经网络的高速计算机生成的全息术OPTICS LETTERS
OPTICS LETTERSIF3.3
PREAI
分享收藏The significance of serum active matrix metalloproteinase-9 in patients with non-small cell lung cancerLung Cancer
Lung CancerIF0
PREAI
分享收藏Controlling image size as a function of distance and wavelength in Fresnel-transform reconstruction of digital hologramsOPTICS LETTERS
OPTICS LETTERSIF3.3
PREAI
分享收藏
查看更多内容