Hyperspectral Dual-Comb Compressive Ghost Imaging with Deep Learning Reconstruction
A paper in Light: Science & Applications combines dual combs with compressive ghost imaging and uses deep learning reconstruction to achieve hyperspectral imaging.
Optical and infrared remote sensing, remote sensing imagery, and target perception; includes AI analysis of optical remote sensing data, but excludes radar remote sensing unrelated to optics.
A paper in Light: Science & Applications combines dual combs with compressive ghost imaging and uses deep learning reconstruction to achieve hyperspectral imaging.
A team led by Peng Xie at the Shanghai Institute of Optics and Mechanics has made progress in multidimensional multiplexed optical computing, improving the parallelism of optical computing.
Why we recommend it: The original article provides specific data and details that help assess the actual progress in this direction