In this article, we perform a review of the state-of-the-art of hybrid machine learning in
medical imaging. We start with a short summary of the general developments of the past in …

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 …

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 …

Computational imaging systems algorithmically post-process acquisition images either to
reveal physical quantities of interest or to increase image quality, eg, deblurring. Designing …

Tasks across diverse application domains can be posed as large-scale optimization
problems, these include graphics, vision, machine learning, imaging, health, scheduling …

Diffractive snapshot hyperspectral imaging based on the deep optics framework has been
striving to capture the spectral images of dynamic scenes. However, existing deep optics …

Unwanted camera obstruction can severely degrade captured images, including both scene
occluders near the camera and partial occlusions of the camera cover glass. Such …

While conventional cameras offer versatility for applications ranging from amateur
photography to autonomous driving, computational cameras allow for domain-specific …

Most camera lens systems are designed in isolation, separately from downstream computer
vision methods. Recently, joint optimization approaches that design lenses alongside other …