Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …

Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for
disease detection. Advances in digital pathology and developments in computer vision …

Nonlinear encoding of optical information can be achieved using various forms of data
representation. Here, we analyze the performances of different nonlinear information …

Wireless sensing of the wave propagation direction from radio sources lays the foundation
for communication, radar, navigation, etc. However, the existing signal processing paradigm …

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path
length information of transparent specimens for various applications in biology, materials …

Scalable, high-capacity, and low-power computing architecture is the primary assurance for
increasingly manifold and large-scale machine learning tasks. Traditional electronic artificial …

Image denoising, one of the essential inverse problems, targets to remove noise/artifacts
from input images. In general, digital image denoising algorithms, executed on computers …

Complex field imaging, which captures both the amplitude and phase information of input
optical fields or objects, can offer rich structural insights into samples, such as their …

Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront
distortions, with applications ranging from imaging to beam focusing. Here, we present a …

Diffractive deep neural networks (D2NNs) are composed of successive transmissive layers
optimized using supervised deep learning to all-optically implement various computational …