The growing demand for electronic devices, smart devices, and the Internet of Things
constitutes the primary driving force for marching down the path of decreased critical …

Recent years have witnessed the unprecedented progress of deep learning applications in
digital holography (DH). Nevertheless, there remain huge potentials in how deep learning …

Holography provides access to the optical phase. The emerging compressive phase
retrieval approach can achieve in-line holographic imaging beyond the information-theoretic …

Deep learning-based image reconstruction methods have achieved remarkable success in
phase recovery and holographic imaging. However, the generalization of their image …

Existing applications of deep learning in computational imaging and microscopy mostly
depend on supervised learning, requiring large-scale, diverse and labelled training data …

While recent research has shown that holographic displays can represent photorealistic 3D
holograms in real time, the difficulty in acquiring high-quality real-world holograms has …

Holographic near-eye displays offer unprecedented capabilities for virtual and augmented
reality systems, including perceptually important focus cues. Although artificial intelligence …

Deep learning has been develo** rapidly, and many holographic applications have been
investigated using deep learning. They have shown that deep learning can outperform …

Computational methods have been established as cornerstones in optical imaging and
holography in recent years. Every year, the dependence of optical imaging and holography …

The purpose of this tutorial is to teach the method of digital in-line holography (DIH) as a
means to characterize aerosol particles in an in-situ manner. The scope is limited to the …