With the rapid development of high-speed communication and artificial intelligence
technologies, human perception of real-world scenes is no longer limited to the use of small …

Deep learning has been revolutionizing information processing in many fields of science
and engineering owing to the massively growing amounts of data and the advances in deep …

Cameras are designed with a complicated tradeoff between image quality (eg sharpness,
contrast, color fidelity), and practical considerations such as cost, form factor, and weight …

Imaging depth and spectrum have been extensively studied in isolation from each other for
decades. Recently, hyperspectral-depth (HS-D) imaging emerges to capture both …

Monocular depth estimation remains a challenging problem, despite significant advances in
neural network architectures that leverage pictorial depth cues alone. Inspired by depth from …

Sorption-based atmospheric water harvesting (SAWH) has received unprecedented
attention as a future water and energy platform. However, the water productivity of SAWH …

Deep optical optimization has recently emerged as a new paradigm for designing
computational imaging systems using only the output image as the objective. However, it …

High-resolution single-photon imaging remains a big challenge due to the complex
hardware manufacturing craft and noise disturbances. Here, we introduce deep learning into …

Optical imaging and sensing systems based on diffractive elements have seen massive
advances over the last several decades. Earlier generations of diffractive optical processors …

In traditional imaging system design, the optical lens is often optimized toward the artificial
optimization target like modulation transfer function and field-of-view (FoV). This usually …