Deep learning in the context of nano-photonics is mostly discussed in terms of its potential for inverse design of photonic devices or nano-structures. Many of the recent works on …
Imaging can take many forms—from optical microscopes and telescopes through ultrasonography to X-ray tomography. However, regardless of the imaging modality, the …
The last decade has seen the development of a wide set of tools, such as wavefront shaping, computational or fundamental methods, that allow us to understand and control …
Since their inception in the 1930–1960s, the research disciplines of computational imaging and machine learning have followed parallel tracks and, during the last two decades …
Optical imaging has had a central role in elucidating the underlying biological and physiological mechanisms in living specimens owing to its high spatial resolution, molecular …
Deep learning has been proven to yield reliably generalizable solutions to numerous classification and decision tasks. Here, we demonstrate for the first time to our knowledge …
Time-of-flight three-dimensional (3D) imaging has applications that range from industrial inspection to motion tracking. Depth is recovered by measuring the round-trip flight time of …
Computational imaging through scatter generally is accomplished by first characterizing the scattering medium so that its forward operator is obtained and then imposing additional …
The newly emerging field of wave front shaping in complex media has recently seen enormous progress. The driving force behind these advances has been the experimental …