Complex-Domain Neural Network Advances Large-Scale Coherent Imaging

A team of researchers from China's Beijing Institute of Technology, the California Institute of Technology, and the University of Connecticut has augmented large-scale coherent imaging with a complex-domain neural network. The researchers integrated a two-dimensional complex convolution unit and complex activation function into a network that generates multidimensional representations of complex wavefront. They also created a multi-source noise model that advances domain-adaptation ability from synthetic to real data. The researchers found the approach reduces exposure time and data volume by an order of magnitude without hindering efficiency or reconstruction quality. [ Click on the image to read the full article ]