  We are concerned with the inverse scattering problems associated with
incomplete measurement data. It is a challenging topic of increasing importance
in many practical applications. Based on a prototypical working model, we
propose a machine learning based inverse scattering scheme, which integrates a
CNN (convolution neural network) for the data retrieval. The proposed method
can effectively cope with the reconstruction under limited-aperture and/or
phaseless far-field data. Numerical experiments verify the promising features
of our new scheme.
